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Elsevier

Books in Bioinformatics and computational biology

  • Human-AI-Cognitive Intelligence Software, System, and Services for Quality Assurance

    Theories and Methods with Systems Thinking for Behaviour Change in the Medical Decision-Making Pathway
    • 1st Edition
    • Pantea Keikhosrokiani
    • English
    Habit-based Behavior Change Medical Information Support System and Artificial Intelligence: Theories, Methods, and Data Analytics Approach provides a guideline to design and implement Habit-based Behavior Change Support Systems (HBCSS) which can change patient’s unhealthy habits to prevent the development of diseases. It presents theories, methods, management, and data analytics approach required to design, implement, and prescribe the use of HBCSS for several diseases’ management.It discusses topics such as theories of behavior change, ontologies and knowledge management, data mining, privacy and security, descriptive and prescription analytics. In addition, it discusses how to measure habit-change, future directions of the field, and case studies based on real-world examples.It is a valuable resource for clinicians, researchers, students, and member of the biomedical and medical fields who want to learn more about the use of medical systems to improve patients’ health.

  • Artificial Intelligence Based Primary Care

    Artificial Intelligence and Human Cognition in General Practice and Family Medicine
    • 1st Edition
    • Anthony C. Chang + 5 more
    • English
    Artificial Intelligence Based Primary Care: Artificial Intelligence and Human Cognition in General Practice and Family Medicine provides a comprehensive look into the integration of artificial intelligence within primary care. This book aims to bridge the gap between data scientists and primary care clinicians by presenting potential AI applications, implementation challenges, and real-world clinical scenarios in an accessible manner. Comprised of 5 sections and 20 chapters, it offers both theoretical insights and practical guidance for family medicine practitioners.Additi... the book includes a chapter dedicated to a day in the life of a General Practitioner, showcasing the practical impact of AI. It also features an extra compendium listing the Top 100 articles and best books on Artificial Intelligence. This resource is invaluable for academics, researchers, and clinicians eager to expand their knowledge in this emerging field.

  • Advances in Structural Biology

    Applications in Protein Structure, Function, and Disease
    • 1st Edition
    • Anas Shamsi + 3 more
    • English
    Advances in Structural Biology: From Protein Structures to Function and Disease offers a comprehensive, practical resource that bridges the latest experimental and computational approaches in structural biology. Backed by real-world case studies, the book demonstrates how these technologies can be utilized to serve a range of biological needs. The content spans foundational principles of protein structure and bioinformatics tools, cutting-edge methodologies such as MicroED and Cryo-EM, and the transformative role of artificial intelligence and big data analytics in structural biology. It also considers applications including drug discovery, vaccine development, antiviral therapy, personalized medicine, and the structural basis of aging and neurodegenerative diseases.Readers will find detailed investigation into the latest developments in structural and computational biology, including insights into integrative methodologies that combine both traditional and emerging technologies. This resource is invaluable for advanced students, researchers, and professionals aiming to harness structural biology for innovative solutions in precision medicine and translational research.

  • Statistical Bioinformatics with R

    • 2nd Edition
    • Sunil K. Mathur
    • English
    Statistical Bioinformatics with R, Second Edition offers a balanced treatment of statistical theory within the context of bioinformatics applications. The book goes beyond gene expression and sequence analysis to include a careful integration of statistical theory in bioinformatics. The inclusion of R codes, along with the development of advanced methodologies such as Bayesian and Markov models, equips students with a solid foundation for conducting bioinformatics research. Sections incorporate the latest advancements in bioinformatics and statistical methodologies, including new chapters on cutting-edge topics such as high-throughput sequencing data analysis, AI/machine learning applications in bioinformatics, and advanced statistical methods.From new and updated practical examples and case studies that illustrate real-world applications of statistical techniques to bioinformatic problems to enhanced end-of-chapter exercises, detailed code annotations, and an improved companion website with supplementary materials, including datasets and R scripts, this book is a valuable resource for both self-study and formal coursework, fostering a deeper understanding of statistical bioinformatics and equipping readers with the skills needed to tackle complex biological data analysis challenges.

  • Genome Analysis

    Principles and Methods
    • 1st Edition
    • Dev Bukhsh Singh + 1 more
    • English
    Genome Analysis: Principles and Methods provides recent and advanced information about genome analysis approaches and techniques to study and annotate the structure and function of the genome. It is a compendium of important topics such as NGS analysis, genome fragmentation and assembly, metagenomics, cloning and expression, physical marker analysis, transcriptome data analysis, sequence alignment and comparison, evolutionary analysis, SNP analysis, genome-based disease diagnosis and therapies, micro-RNAs, pharmacogenomics, genetic approaches to disease intervention, and challenges with opportunities in genome analysis and genomics, etc.The latest developments in the field are discussed, and key concepts are introduced to ensure readers understand advanced concepts and methodologies in the area. The book serves as a valuable guide to the present, emerging, and evolving research methodologies in the field.

  • Digital Health Maturity: Quality, Interoperability, and Innovation

    • 1st Edition
    • Siaw-Teng Liaw + 3 more
    • English
    Digital Health Maturity: Quality, Interoperability, and Innovation provides a roadmap to move from endless pilots and ad hoc system purchase to a systematic, stepwise, and integrated approach to increasing digital health capacity. Specific guidelines, tools, and use cases are discussed to show how the digital health maturity metamodel (DHM3) can be put into actual practice. The book discusses topics such as foundations of digital health and how to put them into practice; organizational considerations for implementation; and best practices, tools, and pitfalls to avoid. In addition, it discusses the future of digital transformation and the impact of a global adherence to digital health. It is a valuable resource for researchers, students, policy makers, governments and anyone who is interested in learning more about digital health and its benefits worldwide.

  • Healthcare Applications of Neuro-Symbolic Artificial Intelligence

    • 1st Edition
    • Boris Galitsky
    • English
    Healthcare Applications of Neuro-Symbolic Artificial Intelligence provides a comprehensive introduction to the field of neuro-symbolic (NS) artificial intelligence (AI), presenting the most recent advances in deep learning and integration of NS systems and large language models (LLMs). This book evaluates traditional approaches, current approaches, as well as the author’s own approach to NS, to create hybrid architectures and reasoning techniques to overcome the limitations of most existing AI systems such as deep learning, neural networks, and symbolic AI.This book will be a welcome resource for researchers and graduate students in AI, natural language processing, and biomedical informatics, as well as professionals in software development looking to redesign current systems to leverage LLMs through the health application of NS architecture.

  • Multi-Omics Technology in Human Health and Diseases

    Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics, Radiomics, Multi-omics
    • 1st Edition
    • Muzafar A Macha + 2 more
    • English
    Multi-Omics Technology in Human Health and Diseases: Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics, Radiomics, Multi-omic offers an advanced exploration into the comprehensive understanding of disease etiology and prognosis through multiomics approaches. This authoritative volume delves into the applications of multiomics technology in elucidating complex human health conditions and diseases. It introduces the technology's potential for biomarker identification, drug discovery, and disease prognostication. For a thorough understanding of human health and diseases, particularly cancer, it is essential to integrate knowledge of molecular biomarkers across multiple omics levels, including the genome, epigenome, transcriptome, proteome, and metabolome. This resource addresses the current gaps in knowledge among students and researchers, providing in-depth coverage of multiomics technology and its implementation in scientific research and discovery.Multi-Omic... Technology in Human Health and Diseases: Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics, Radiomics, Multi-omics is a pioneering resource that presents cutting-edge information on contemporary multiomics technologies for big data interpretation and their applications in deciphering complex human pathobiology. This comprehensive guide is indispensable for researchers, academics, students, and industry professionals alike.

  • Deep Learning in Genetics and Genomics

    Volume 1: Foundations and Introductory Applications
    • 1st Edition
    • Khalid Raza
    • English
    Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our understanding of the genetic code, gene regulation, and the broader genomics landscape. The book not only covers the most up-to-date advancements in the field of deep learning in genetics and genomics, but also a wide spectrum of (sub) topics including medical and clinical genetics, predictive medicine, transcriptomic, and gene expression studies. In 21 chapters Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications describes how AI and DL have become increasingly useful in genetics and genomics research where both play a crucial role by accelerating research, improving the understanding of the human genome, and enabling personalized healthcare. From the fundamentals concepts and practical applications of deep learning algorithms to a wide range of challenging problems from genetics and genomics, Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications creates a better knowledge of the biological and genetics mechanisms behind disease illnesses and improves the forecasting abilities using the different methodologies described. This title offers a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning-based approaches in genetics and genomics, helping researchers process and interpret vast amounts of genetic data, identify patterns, and make discoveries that would be challenging or impossible using traditional methods.

  • Deep Learning in Genetics and Genomics

    Volume 2: Advanced Applications
    • 1st Edition
    • Khalid Raza
    • English
    Deep Learning in Genetics and Genomics: Vol. 2 (Advanced Applications) delves into the Deep Learning methods and their applications in various fields of studies, including genetics and genomics, bioinformatics, health informatics and medical informatics generating the momentum of today's developments in the field. In 25 chapters this title covers advanced applications in the field which includes deep learning in predictive medicines), analysis of genetic and clinical features, transcriptomics and gene expression patterns analysis, clinical decision support in genetic diagnostics, deep learning in personalised genomics and gene editing, and understanding genetic discoveries through Explainable AI. Further, it also covers various deep learning-based case studies, making this book a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning based approaches. This volume is not only a valuable resource for health educators, clinicians, and healthcare professionals but also to graduate students of genetics, genomics, biology, biostatistics, biomedical sciences, bioinformatics, and interdisciplinary sciences.

  • The Three Functional States of Proteins

    Structured, Intrinsically Disordered, and Phase Separated
    • 1st Edition
    • Timir Tripathi + 1 more
    • English
    The Three Functional States of Proteins explores how structured proteins, intrinsically disordered proteins, and phase separated proteins contribute to the complexity of cellular life, and offers insights into their roles in both health and disease. It discusses the latest research findings and highlight groundbreaking discoveries and innovative methodologies used to study these protein states.Traditionally... the different states of proteins have been defined based on their structures and functions. However, it is becoming increasingly clear that these criteria alone may not be sufficient to capture the complex and multifaceted properties of these molecules. Definitions based on thermodynamics and kinetics are now recognized as potentially more appropriate for comprehensively understanding protein states. Emerging evidence indicates that under physiological conditions, a majority of proteins possess the capability to exist in and transition between the native, droplet, and amyloid states. These distinct states play crucial roles in various cellular functions, influenced significantly by their physicochemical and structural properties. The book also considers the interactions among these states and discusses how their internal organization as individual molecules, as well as their collective organization as molecular assemblies are stabilized. Furthermore, it examines the processes by which these states are formed and the cellular functions associated with each specific state.

  • Mining Biomedical Text, Images and Visual Features for Information Retrieval

    • 1st Edition
    • Sujata Dash + 3 more
    • English
    Mining Biomedical Text, Images and Visual Features for Information Retrieval provides broad coverage of the concepts, themes, and instrumentalities of the important, evolving area of biomedical text, images, and visual features towards information retrieval. The book aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research. Topics covered include Internet of Things for health informatics; data privacy; smart healthcare; medical image processing; 3D medical images; evolutionary computing; deep learning; medical ontology; linguistic indexing; lexical analysis; and domain specific semantic categories in biomedical applications. This is a valuable resource for researchers and graduate students who are interested to learn more about data mining techniques to improve their research work.

  • Machine Learning Models and Architectures for Biomedical Signal Processing

    • 1st Edition
    • Suman Lata Tripathi + 3 more
    • English
    Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase the efficiency of hardware and architecture design for biomedical signal processing and signal processing techniques.

  • Next Generation eHealth

    Applied Data Science, Machine Learning and Extreme Computational Intelligence
    • 1st Edition
    • Miltiadis Lytras + 3 more
    • English
    Next Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence discusses the emergence, the impact, and the potential of sophisticated computational capabilities in healthcare. This book provides useful therapeutic targets to improve diagnosis, therapies, and prognosis of diseases, as well as helping with the establishment of better and more efficient next-generation medicine and medical systems. Machine learning as a field greatly contributes to next-generation medical research with the goal of improving medicine practices and medical Systems. As a contributing factor to better health outcomes, this book highlights the need for advanced training of professionals from various health areas, clinicians, educators, and social professionals who deal with patients. Content illustrates current issues and future promises as they pertain to all stakeholders, including informaticians, professionals in diagnostics, key industry experts in biotech, pharma, administrators, clinicians, patients, educators, students, health professionals, social scientists and legislators, health providers, advocacy groups, and more. With a focus on machine learning, deep learning, and neural networks, this volume communicates in an integrated, fresh, and novel way the impact of data science and computational intelligence to diverse audiences.

  • Artificial Intelligence in Biomedical and Modern Healthcare Informatics

    • 1st Edition
    • M. A. Ansari + 4 more
    • English
    Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis, its practical approach in healthcare, and gives insight into different wearable sensors and its device module to help doctors and their patients in enhanced healthcare system.The primary goal of this book is to detect difficulties and their solutions to medical practitioners for the early detection and prediction of any disease.The 56 chapters in the volume provide beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications.With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare.

  • Planning, Writing and Reviewing Medical Device Clinical and Performance Evaluation Reports (CERs/PERs)

    A Practical Guide for the European Union and Other Countries
    • 1st Edition
    • Joy Frestedt
    • English
    A Practical Guide to Planning, Writing, and Reviewing Medical Device Clinical Evaluation Reports guides readers through clinical data evaluation of medical devices that is in compliance with the EU MDR requirements and other similar regulatory requirements throughout the world. This book brings together knowledge learned as the author constructed hundreds of CERs and taught thousands of learners on how to conduct clinical data evaluations. This book will support training for clinical engineers, clinical evaluation scientists, and experts reviewing medical device CERs, and will help individual writers, teams and companies to develop stronger, more robust CERs.

  • Applied Multivariate Statistical Analysis in Medicine

    • 1st Edition
    • Jingmei Jiang
    • English
    Applied Multivariate Statistical Analysis in Medicine provides a multivariate conceptual framework that allows readers to understand the interconnectivity and interrelations among variables, which maintains the intrinsic precision of statistical theories. With a strong focus on the fundamental concepts of multivariate statistical analysis, the book also gives insight into the applications of multivariate distribution in biomedical fields. In 14 chapters, Applied Multivariate Statistical Analysis in Medicine covers the main topics of multivariate analysis methods widely used in health science research. The content is organized progressively from fundamental concepts to sophisticated methods. It begins with basic descriptive statistics in multivariate analysis and follows with parameter estimation, in addition to the hypothesis testing of a multivariate normal distribution, which has heavy applications in biomedical fields where the relationships among approximately normal variables are of great interest. Keeping mathematics to a minimum, considerable emphasis is placed on explanations and real-world applications of core principles to maintain a good balance between introducing theory and cultivating problem-solving skills. This book is a very valuable reference text for clinicians, medical researchers, and other researchers across medical and biomedical disciplines, all of whom confront increasingly complex statistical methods during the analysis and presentation of their results.

  • Concepts and Techniques in OMICS and System Biology

    • 1st Edition
    • Asmat Farooq + 5 more
    • English
    Concepts and Techniques in OMICS and Systems Biology provides a concise and lucid account on the technical aspects of omics, system biology and their application in fields of different life science.With a strong focus on the fundamental principles understanding of metabolomics, ionomics and system biology, the book also gives an updated account on technical aspects of omics and system biology. Since both omics and systems biology fields are fast advancing filed of biological sciences, its significance and applications need to be understood from the baseline.In 10 chapters Concepts and Techniques in OMICS and Systems Biology introduces the reader to both Proteomics, Metabolomics and Ionomics, and System Biology, the technical applications, describes both the software in for proteomics as metabolomic enumeration and preludes Omics technologies and their applications.The chapters are designed in a well-defined chronology such that readers will understand the concepts and techniques involved in omics and system biology. This compilation will be ideal reading material for students, researchers and people working in the industries related to biological sciences.

  • Reverse Vaccinology

    Concept, Methods and Advancement
    • 1st Edition
    • Jayashankar Das + 3 more
    • English
    Reverse Vaccinology: Concept, Methods, and Advancement presents the development strategy of new vaccines through genome sequencing bioinformatics analysis. This book promises to revolutionize vaccine development, especially for pathogens to which the classical applications of Pasteur’s principles have failed, and it is explained in detail in this book.This book is split into three sections: the first, Concept, brings the basis of reverse vaccinology, vaccine antigen discovery, and subunit vaccine; the second, Tools and Methods, describes immunoinformatic, proteomics for epitope-vaccine design, databases, network analysis, machine learning, and NGS-driven antigen screening technology; and the last one, Disease Case Study, discusses real-world examples in the development of new vaccines for diverse diseases.It is a valuable resource for bioinformaticians, researchers, students, and members of the biomedical and medical fields who want to learn more about a new and agile process for the development of new vaccines.

  • Recent Trends in Fractional Calculus and Its Applications

    • 1st Edition
    • Praveen Agarwal + 2 more
    • English
    Recent Trends in Fractional Calculus and Its Applications addresses the answer to this very basic question: "Why is Fractional Calculus important?" Until recent times, Fractional Calculus was considered as a rather esoteric mathematical theory without applications, but in the last few decades there has been an explosion of research activities on the application of Fractional Calculus to very diverse scientific fields ranging from the physics of diffusion and advection phenomena, to control systems to finance and economics. An important part of mathematical modelling of objects and processes is a description of their dynamics.The term Fractional Calculus is more than 300 years old. It is a generalization of the ordinary differentiation and integration to noninteger (arbitrary) order. The subject is as old as the calculus of differentiation and goes back to times when Leibniz, Gauss, and Newton invented this kind of calculation. Several mathematicians contributed to this subject over the years. People like Liouville, Riemann, and Weyl made major contributions to the theory of Fractional Calculus. In recent decades the field of Fractional Calculus has attracted the interest of researchers in several areas, including mathematics, physics, chemistry, engineering, finance, and social sciences.

  • Resilient Health

    Leveraging Technology and Social Innovations to Transform Healthcare for COVID-19 Recovery and Beyond
    • 1st Edition
    • Judy Kuriansky + 1 more
    • English
    Resilient Health: Leveraging Technology and Social Innovations to Transform Healthcare for COVID-19 Recovery and Beyond presents game-changing and disruptive technological innovations and social applications in physical and mental healthcare around the world for the post-COVID age and beyond, addressing the urgent need for care. In this first-of-its kind comprehensive volume, experts and stakeholders from all sectors - government and the public and private sectors - offer models and frameworks for policy, programming, and financing to transform healthcare, address inequities, close the treatment gap, and “build back better,” especially for under-resourced vulnerable communities globally, to “leave no one behind” and advance development globally. Contributions from world experts cover 8 essential parts: The context and challenges for resilient health systems to shape the future; developments and directions (AI, VR, MR, IVAs and more); an innovations toolbox, also targeted for special populations and settings (women, youth, ageing, migrants, disabled persons, indigenous peoples, in the workplace); the role of stakeholders (governments, the United Nations bodies, and the public and private sector); forums and networks; innovative financing; resources, lessons learned and the way forward.

  • Digital Healthcare in Asia and Gulf Region for Healthy Aging and More Inclusive Societies

    Shaping Digital Future
    • 1st Edition
    • Patricia Ordonez de Pablos
    • English
    Digital Healthcare in Asia and Gulf Region for Healthy Aging and More Inclusive Societies: Shaping Digital Future provides insight to the potential of advanced information technologies to build stronger healthcare systems, better quality healthcare services, and more resilient societies. The book covers two important regions: Gulf Region (Bahrein, Kuwait, Oman, Qatar, and UAE) and Asia, and explores how these countries develop policies for healthy aging and how digital tools can serve these goals. This book delivers a collection of relevant, innovative research works on digital healthcare, with four main goals: (1) to cover two geographical regions (Asia and Gulf Region) with important advances in digital healthcare; (2) to present case studies in the field of IT and digital health during the pandemic and analyze the lessons from these studies; (3) to evaluate the latest advances in the field of digital healthcare (especially Artificial Intelligence [AI], Big Data, Blockchain, and 5G); and (4) to discuss implications for main stakeholders (patients, doctors, IT experts, directors, and policy managers) and recommendations for policy makers in these two regions and elsewhere.

  • Biological Insights of Multi-Omics Technologies in Human Diseases

    • 1st Edition
    • Aarif Ali + 3 more
    • English
    Biological Insights of Multi-Omics Technologies in Human Diseases provides detailed information about the basics of multi-omic technologies, including ethics, historical perspective, science, drug discovery, and development and metabolism. With a strong focus on the practical application of omics approaches in cancer, cardiovascular, neurology, respiratory, viral, gastroenterology, autoimmune diseases, PCOS and tuberculosis, this book also includes special topics related to COVID-19 and Machine learning approaches. In 13 chapters, this book provides comprehensive coverage of the challenges and opportunities facing the therapeutic implications of multi-omics from academic, regulatory, pharmaceutical, socio-ethical, and economic perspectives.The chapters are designed in a well-defined chronology such that readers will intuitively understand the central idea. This book is an ideal resource for health professionals, scientists and researchers, nutritionists, health practitioners, students, and all those who wish to broaden their knowledge in the allied field.

  • Integrative Omics

    Concept, Methodology, and Application
    • 1st Edition
    • Manish Kumar Gupta + 3 more
    • English
    Integrative Omics: Concept, Methodology and Application provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference provides systemic ‘step-by-step’ coverage that begins with basic concepts from Omic to Multi Integrative Omics approaches followed by applications and emerging and future trends. All areas of Omics are covered, including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics, technology policy, and society research. This book covers recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science.

  • Open Electronic Data Capture Tools for Medical and Biomedical Research and Medical Allied Professionals

    • 1st Edition
    • Ashish Pundhir + 2 more
    • English
    Open Electronic Data Capture Tools for Medical and Biomedical Research and Medical Allied Professionals explains the step-by-step of collecting and treating research data in a didactic manner. The book discusses four freely available data capture tools whose common feature is data collection and entry being done simultaneously rather than separately, thus saving resources and minimizing potential errors. It highlights the comparative features of each data capture tool, helping readers to understand the advantage and disadvantage of each one to decide which tool can be used to fulfill their needs.This is a valuable resource for researchers, students, and members of the biomedical and medical fields who need to learn more about data mining and management to improve the quality of their research work.

  • Artificial Intelligence in Medicine

    From Ethical, Social, and Legal Perspectives
    • 1st Edition
    • Joseph JY Sung + 1 more
    • English
    Artificial Intelligence in Medicine: From Ethical, Social, and Legal Perspectives provides answers on how to improve acceptance and diminish the anxiety of the use of AI-assisted medicine. Through a series of social, ethical, and legal discussions from clinicians, social scientists, ethicists, and legal experts, this important reference has coverage that includes good data custodianship and stewardship, data access, data bias, data & healthcare equity, privacy and confidentiality, algorithmic understanding, and regulatory guidance, accountability, and legal responsibility.This reference will explain to healthcare providers how AI will enhance healthcare, will introduce to scientists and researchers the ethical and social aspect of AI that needs to be addressed, and will urge policymakers and health authorities to consider the legal framework needed to implement AI technology in healthcare.

  • Applications of Artificial Intelligence in Healthcare and Biomedicine

    • 1st Edition
    • Abdulhamit Subasi
    • English
    Applications of Artificial Intelligence in Healthcare and Biomedicine provides ​updated knowledge on the applications of artificial intelligence in medical image analysis. In 16 chapters, it presents artificial applications in Electrocardiogram (ECG), Electroencephalogram (EEG) and Electromyography (EMG), signal analysis, Computed Tomography (CT), Magnetic Resonance Imaging (MR), and Ultrasound image analysis. It equips researchers with tools for early breast cancer detection from mammograms using artificial intelligence (AI), AI models to detect lung cancer using histopathological image, and a deep learning-based approach to get a proper and faster diagnosis of the Optical Coherence Tomography (OCT) images.In addition, it presents 3D medical image analysis using 3D Convolutional Neural Networks (CNNs). Final sections cover an AI-based approach to forecast diabetes patients' hospital re-admissions. This is a valuable resource for clinicians, researchers, and healthcare professionals who are interested in learning more about the applications of Artificial Intelligence and its impact in medical/biomedical image analysis.

  • A Biologist’s Guide to Artificial Intelligence

    Building the foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences
    • 1st Edition
    • Ambreen Hamadani + 3 more
    • English
    A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future.This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms.

  • Artificial intelligence, Big data, blockchain and 5G for the digital transformation of the healthcare industry

    A movement Toward more resilient and inclusive societies
    • 1st Edition
    • Patricia Ordonez de Pablos + 1 more
    • English
    ​Artificial intelligence, Big data, Blockchain and 5G for Digital Transformation of Healthcare Industry: A Movement Towards More Resilient and Inclusive Societies delivers a collection of relevant innovative research on digital healthcare, with a three mains goals: 1) study the successes and failures in the field of IT and digital health during the pandemic, and analyze the lessons from these cases; 2) discuss the latest advances in the field of digital healthcare, with a special focus on Artificial Intelligence, Big Data, Blockchain and 5G; and 3) discuss implications for main stakeholders (patients, doctors, IT experts, directors, policy managers.The global outbreak caused by covid-19 caused global disruption in societies, healthcare systems, and economies around the world. This book provides insight to Researchers, clinicians, CEOs and policymakers who need to learn from the failures and successes and exploit the potential of advanced information technologies to build stronger healthcare systems, better quality healthcare services, and more resilient societies.

  • Handbook of Whale Optimization Algorithm

    Variants, Hybrids, Improvements, and Applications
    • 1st Edition
    • Seyedali Mirjalili
    • English
    Handbook of Whale Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides the most in-depth look at an emerging meta-heuristic that has been widely used in both science and industry. Whale Optimization Algorithm has been cited more than 5000 times in Google Scholar, thus solving optimization problems using this algorithm requires addressing a number of challenges including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters to name a few. This handbook provides readers with in-depth analysis of this algorithm and existing methods in the literature to cope with such challenges. The authors and editors also propose several improvements, variants and hybrids of this algorithm. Several applications are also covered to demonstrate the applicability of methods in this book.

  • AI in Clinical Practice

    A Guide to Artificial Intelligence and Digital Medicine
    • 1st Edition
    • Giampaolo Collecchia + 1 more
    • English
    **Selected for 2026 Doody's Core Titles as an Essential Purchase in Medical Informatics**AI in Clinical Practice: A Guide to Artificial Intelligence and Digital Medicine explains how artificial intelligence is applied to medicine, illustrating not only its enormous potential but also ancillary issues and the limits and risks inherent in its use on a large scale. The book focuses on the intersection between medicine and AI and its implications on the impact of human health care delivery. Topics discussed include wearable devices, health data, Internet of Things, virtual reality, robotic assistance system, and digital intelligence in the health sector. Additionally, sections discuss diagnostics and decision-making systems and machine/deep learning in clinical setting.This is a valuable resource for clinicians, researchers, students and members of the biomedical and medical fields who want to learn more about the use of AI to improve patient care.

  • Artificial Intelligence in Clinical Practice

    How AI Technologies Impact Medical Research and Clinics
    • 1st Edition
    • Chayakrit Krittanawong
    • English
    Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN. This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine.

  • Active Learning for Digital Transformation in Healthcare Education, Training and Research

    • 1st Edition
    • Miltiadis Lytras + 1 more
    • English
    Active Learning for Digital Transformation in Healthcare Education, Training and Research discusses the potential of advanced training of health professionals as a contributing factor to improve treatment outcomes. By reading this book, professionals who deal with patients with low health literacy will be prepared to promote better access to digital tools, understand the habits of users of health services, and empower engagement. The book contains a set of techniques and instruments associated with health literacy, communication skills and personal development that will enable their application in good daily practices and assist healthcare professionals to promote digital transformation to patients. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about how they can be an effective agent of change in healthcare.

  • Modeling of Post-Myocardial Infarction

    ODE/PDE Analysis with R
    • 1st Edition
    • William E. Schiesser
    • English
    Modeling of Post-Myocardial Infarction: ODE/PDE Analysis with R presents mathematical models for the dynamics of a post-myocardial (post-MI), aka, a heart attack. The mathematical models discussed consist of six ordinary differential equations (ODEs) with dependent variables Mun; M1; M2; IL10; Tα; IL1. The system variables are explained as follows: dependent variable Mun = cell density of unactivated macrophage; dependent variable M1 = cell density of M1 macrophage; dependent variable M2 = cell density of M2 macrophage; dependent variable IL10 = concentration of IL10, (interleuken-10); dependent variable Tα = concentration of TNF-α (tumor necrosis factor-α); dependent variable IL1 = concentration of IL1 (interleuken-1). The system of six ODEs does not include a spatial aspect of an MI in the cardiac tissue. Therefore, the ODE model is extended to include a spatial effect by the addition of diffusion terms. The resulting system of six diffusion PDEs, with x (space) and t (time) as independent variables, is integrated (solved) by the numerical method of lines (MOL), a general numerical algorithm for PDEs.

  • Deep Learning in Personalized Healthcare and Decision Support

    • 1st Edition
    • Harish Garg + 1 more
    • English
    Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth.

  • Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry

    • 1st Edition
    • Patricia Ordonez de Pablos + 1 more
    • English
    Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry discusses innovative conceptual frameworks, tools and solutions to tackle the challenges of mitigating major disruption caused by COVID-19 in the healthcare sector and society. It emphasizes global case studies and empirical studies, providing a comprehensive view of best lessons on digital tools to manage the health crisis. The book focuses on the role of advances in digital and collaborative technologies to offer rapid and effective tools for better health solutions for new and emerging health problems. Researchers, students, policymakers and members of the biomedical and medical fields will find this information invaluable. Specially, it pays attention to how information technologies help us in the current global health emergency and the coronavirus epidemic response, gaining more understanding of the new coronavirus and helping to contain the outbreak. In addition, it explores how these new tools and digital health solutions can support the economic and social recovery in the post-pandemic world.

  • Digital Transformation in Healthcare in Post-COVID-19 Times

    • 1st Edition
    • Miltiadis Lytras + 2 more
    • English
    Digital Transformation in Healthcare in Post-Covid19 Times discusses recent advances in patient care and offers critical comparative insights into their application across multiple domains in healthcare. By showcasing key problems, best practices and emerging challenges, the book offers a state-of-art review of opportunities and prospects in the process of delivering smart sustainable healthcare services. Topics discussed include healthcare challenges in the post-COVID-19 era, enabling technologies for digital transformation, value driven approaches to the delivery of patient centric top-quality health services, and analytics and enhanced decision making. In addition, the book updates knowledge on best practices for training towards digital transformation and sustainable health. This is a valuable resource for healthcare professionals, medical doctors, researchers, graduate students and members of the biomedical field who are interested in learning more about the use of emerging technologies in healthcare.

  • All About Bioinformatics

    From Beginner to Expert
    • 1st Edition
    • Yasha Hasija
    • English
    All About Bioinformatics: From Beginner to Expert provides readers with an overview of the fundamentals and advances in the _x001F_field of bioinformatics, as well as some future directions. Each chapter is didactically organized and includes introduction, applications, tools, and future directions to cover the topics thoroughly. The book covers both traditional topics such as biological databases, algorithms, genetic variations, static methods, and structural bioinformatics, as well as contemporary advanced topics such as high-throughput technologies, drug informatics, system and network biology, and machine learning. It is a valuable resource for researchers and graduate students who are interested to learn more about bioinformatics to apply in their research work.

  • Unleashing the Potentials of Blockchain Technology for Healthcare Industries

    • 1st Edition
    • Amar Das + 4 more
    • English
    Unleashing the Potentials of Blockchain Technology for Healthcare Industries discusses blockchain and its adaptation in healthcare industries to provide a secured framework to safeguard healthcare data, both patient and hospital data. The book integrates key pillars of blockchain such as foundations, architecture, smart contracts, adoption, standards, service (BaaS), security, consensus algorithms, drug discovery process, among others, for fortifying the current practices in the healthcare industries. In addition, it offers solutions to the pressing issues currently being faced by the healthcare processes due to the COVD-19 pandemic. This will be a valuable resource for medical informaticians, researchers, healthcare professionals and members of the biomedical field who are interested in learning more about the potentials of blockchain in healthcare.

  • Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases

    Lessons Learned From COVID-19
    • 1st Edition
    • Esteban A. Hernandez-Vargas + 1 more
    • English
    Mathematical Modeling, Simulations, and Artificial Intelligence for Emergent Pandemic Diseases: Lessons Learned from COVID-19 includes new research, models and simulations developed during the COVID-19 pandemic into how mathematical methods and practice can impact future response. Chapters go beyond forecasting COVID-19, bringing different scale angles and mathematical techniques (e.g., ordinary differential and difference equations, agent-based models, artificial intelligence, and complex networks) which could have potential use in modeling other emergent pandemic diseases. A major part of the book focuses on preparing the scientific community for the next pandemic, particularly the application of mathematical modeling in ecology, economics and epidemiology. Readers will benefit from learning how to apply advanced mathematical modeling to a variety of topics of practical interest, including optimal allocations of masks and vaccines but also more theoretical problems such as the evolution of viral variants.

  • Computational Methods and Deep Learning for Ophthalmology

    • 1st Edition
    • D. Jude Hemanth
    • English
    Computational Methods and Deep Learning for Ophthalmology presents readers with the concepts and methods needed to design and use advanced computer-aided diagnosis systems for ophthalmologic abnormalities in the human eye. Chapters cover computational approaches for diagnosis and assessment of a variety of ophthalmologic abnormalities. Computational approaches include topics such as Deep Convolutional Neural Networks, Generative Adversarial Networks, Auto Encoders, Recurrent Neural Networks, and modified/hybrid Artificial Neural Networks. Ophthalmological abnormalities covered include Glaucoma, Diabetic Retinopathy, Macular Degeneration, Retinal Vein Occlusions, eye lesions, cataracts, and optical nerve disorders. This handbook provides biomedical engineers, computer scientists, and multidisciplinary researchers with a significant resource for addressing the increase in the prevalence of diseases such as Diabetic Retinopathy, Glaucoma, and Macular Degeneration.

  • Clinical Decision Support and Beyond

    Progress and Opportunities in Knowledge-Enhanced Health and Healthcare
    • 3rd Edition
    • Robert Greenes + 1 more
    • English
    Clinical Decision Support and Beyond: Progress and Opportunities in Knowledge-Enhanced Health and Healthcare, now in its third edition, discusses the underpinnings of effective, reliable, and easy-to-use clinical decision support systems at the point of care as a productive way of managing the flood of data, knowledge, and misinformation when providing patient care. Incorporating CDS into electronic health record systems has been underway for decades; however its complexities, costs, and user resistance have lagged its potential. Thus it is of utmost importance to understand the process in detail, to take full advantage of its capabilities. The book expands and updates the content of the previous edition, and discusses topics such as integration of CDS into workflow, context-driven anticipation of needs for CDS, new forms of CDS derived from data analytics, precision medicine, population health, integration of personal monitoring, and patient-facing CDS. In addition, it discusses population health management, public health CDS and CDS to help reduce health disparities. It is a valuable resource for clinicians, practitioners, students and members of medical and biomedical fields who are interested to learn more about the potential of clinical decision support to improve health and wellness and the quality of health care.

  • Practical Data Analytics for Innovation in Medicine

    Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies
    • 2nd Edition
    • Gary D. Miner + 6 more
    • English
    Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics.

  • Applications of Artificial Intelligence in Medical Imaging

    • 1st Edition
    • Abdulhamit Subasi
    • English
    Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis.

  • PDE Modeling of Tissue Engineering and Regenerative Medicine

    Computer Analysis in R
    • 1st Edition
    • William E. Schiesser
    • English
    PDE Modeling of Tissue Engineering and Regenerative Medicine: Computer Analysis in R presents the formulation and computer implementation of mathematical models for the forefront research areas of tissue engineering and regenerative medicine. The mathematical model discussed in this book consists of a system of eight partial differential equations (PDEs) with dependent variables. The computer-based example models are presented through routines coded in R—a quality, open-source scientific computing system that is readily available from the Internet. Formal mathematics is minimized, e.g., no theorems and proofs. Includes detailed examples that the reader can execute on modest computers.

  • Computational Intelligence in Healthcare Applications

    • 1st Edition
    • Rajeev Agrawal + 4 more
    • English
    Computational Intelligence in Healthcare Applications discusses a variety of techniques designed to represent, enhance and empower inter-domain research based on computational intelligence in healthcare. The book serves as a reference for the pervasive healthcare domain which takes into consideration new convergent computing and other applications. The book discusses topics such as mathematical modeling in medical imaging, predictive modeling based on artificial intelligence and deep learning, smart healthcare and wearable devices, and evidence-based predictive modeling. In addition, it discusses computer-aided diagnostic for clinical inferences and pervasive and ubiquitous techniques in healthcare. This book is a valuable resource for graduate students and researchers in medical informatics, however, it is also ideal for members of the biomedical field and healthcare industry who are interested in learning more about novel technologies and their applications in the field.

  • Artificial Intelligence in Bioinformatics

    From Omics Analysis to Deep Learning and Network Mining
    • 1st Edition
    • Mario Cannataro + 4 more
    • English
    Artificial Intelligence in Bioinformatics: From Omics Analysis to Deep Learning and Network Mining reviews the main applications of the topic, from omics analysis to deep learning and network mining. The book includes a rigorous introduction on bioinformatics, also reviewing how methods are incorporated in tasks and processes. In addition, it presents methods and theory, including content for emergent fields such as Sentiment Analysis and Network Alignment. Other sections survey how Artificial Intelligence is exploited in bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, and much more.

  • Practical Biostatistics

    A Step-by-Step Approach for Evidence-Based Medicine
    • 2nd Edition
    • Mendel Suchmacher + 1 more
    • English
    Practical Biostatistics: A Step-by-Step Approach for Evidence-Based Medicine, Second Edition presents a complete resource of biostatistical knowledge meant for health sciences students, researchers and health care professionals. The book's content covers the investigator’s hypothesis, collective health, observational studies, the biostatistics of intervention studies, clinical trials and additional concepts. Chapters are written in a didactic way, making them easier to comprehend by readers with little or no background on statistics. Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision-making using statistical analyses of scientific methods and outcomes to drive further experimentation and diagnosis. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or hands-on guide on how to effectively incorporate biostatistics in clinical trials and research projects.

  • Digital Innovations in Healthcare Education and Training

    • 1st Edition
    • Stathis Th Konstantinidis + 2 more
    • English
    Digital Innovations in Healthcare Education and Training discusses and debates the contemporary knowledge on the evolution of digital education, learning and the web and its integration and role within modern healthcare education and training. The book encompasses topics such as healthcare and medical education theories and methodologies, social learning as a formal and informal digital innovation, and the role of semantics in digital education. In addition, it examines how simulation, serious games, and virtual patients change learnings in healthcare, and how learning analytics and big data in healthcare education leads to personalized learning. Online pedagogy principles and applications, participatory educational design and educational technology as health intervention are bridged together to complement this collaborative effort. This book is a valuable resource for a broad audience, both technical and non-technical, including healthcare and medical tutors, health professionals, clinicians, web scientists, engineers, computer scientists and any other relevant professional interested in using and creating digital innovations for healthcare education and training.

  • Microbiomics

    Dimensions, Applications, and Translational Implications of Human and Environmental Microbiome Research
    • 1st Edition
    • English
    Microbiomics: Dimensions, Applications, and Translational Implications of Human and Environmental Microbiome Research describes a new, holistic approach to microbiomics. International experts provide in-depth discussion of current research methods for studying human, environmental, viral and fungal microbiomes, as well as the implications of new discoveries for human health, nutrition, disease, cancer research, probiotics and in the food and agricultural industries. Distinct chapters covering culturomics and sub-microbiomes, such as the viriome and mycetobiome, provide an integrative framework for the expansion of microbiomics into new areas of application, as well as crosspollination between research areas. Detailed case studies include the use of microbiomics to develop natural products with antimicrobial properties, microbiomic enhancements in food and beverage technology, microbes for bioprotection and biopreservation, microbial tools to reduce antibiotic resistance, and maintenance and cultivation of human microbial communities.