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Elsevier

Books in Data general

  • A Comprehensive Guide to R Programming for Data Analytics

    • 1st Edition
    • Parul Acharya
    • English
    A Comprehensive Guide to R Programming for Data Analytics provides a comprehensive presentation of univariate and multivariate statistical models within the general linear model and generalized linear model framework to analyze simple and complex data using R software. This book presents popular R packages that are used in data mining (e.g., caret-classification and regression, lubridate-dates and times, string-R for string data) and visualization (e.g., ggplot, ggthemes, ggtext). The R packages used to analyze data using a particular statistical model are explained through real-world and publicly available datasets. R codes are presented in a manner that helps readers understand the program code syntax.Examples of real-world data sets from a variety of academic disciplines are provided so that a wide audience can learn R programming to analyze data in their research. The book provides tips, recommendations, and strategies to troubleshoot common issues in R syntax, as well as definitions of key terms. Checkpoints are included to recap the concepts learned in each chapter. The book helps readers enhance their conceptual understanding and practical application of statistical models to real-world datasets, and enables readers to gain competency in R programming, which is an important skill in today’s data-driven market.

  • Probabilistic Modelling for Advanced Data Analysis

    • 1st Edition
    • Amit Kumar Tyagi
    • English
    Probabilistic Modelling for Advanced Data Analysis provides a practical and rigorous guide for data practitioners to effectively implement probabilistic models in real-world scenarios. The book strikes a balance between high-level intuition and technical derivations, offering step-by-step explanations, real-world case studies, and Python implementation examples. The authors offer specific solutions that include modeling and quantifying uncertainty in data-driven decision-making, applying Bayesian inference to real-world problems and implementing scalable probabilistic models for large-scale datasets, all of which contribute to explainable and trustworthy AI.This book presents readers with theoretical foundations and practical applications of probabilistic modeling, providing a structured approach for researchers, data scientists, and industry professionals. It meets the increasing demand for uncertainty-aware AI models, Bayesian inference, and probabilistic graphical models across various fields of research.

  • Essentials of Big Data Analytics

    Applications in R and Python
    • 1st Edition
    • Pallavi Chavan + 2 more
    • English
    Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments.

  • Data Science for Teams

    20 Lessons from the Fieldwork
    • 1st Edition
    • Harris V. Georgiou
    • English
    Managing human resources, time allocation, and risk management in R&D projects, particularly in Artificial Intelligence/Machine Learning/Data Analysis, poses unique challenges. Key areas such as model design, experimental planning, system integration, and evaluation protocols require specialized attention. In most cases, the research tends to focus primarily on one of the two main aspects: either the technical aspect of AI/ML/DA or the teams’ effort, or the typical management aspect and team members’ roles in such a project. Both are equally import for successful real-world R&D, but they are rarely examined together and tightly correlated. Data Science for Teams: 20 Lessons from the Fieldwork addresses the issue of how to deal with all these aspects within the context of real-world R&D projects, which are a distinct class of their own. The book shows the everyday effort within the team, and the adhesive substance in between that makes everything work. The core material in this book is organized over four main Parts with five Lessons each. Author Harris Georgiou goes into the difficulties progressively and dives into the challenges one step at a time, using a typical timeline profile of an R&D project as a loose template. From the formation of a team to the delivery of final results, whether it is a feasibility study or an integrated system, the content of each Lesson revisits hints, ideas and events from real-world projects in these fields, ranging from medical diagnostics and big data analytics to air traffic control and industrial process optimization. The scope of DA and ML is the underlying context for all, but most importantly the main focus is the team: how its work is organized, executed, adjusted, and optimized. Data Science for Teams presents a parallel narrative journey, with an imaginary team and project assignment as an example, running an R&D project from day one to its finish line. Every Lesson is explained and demonstrated within the team narrative, including personal hints and paradigms from real-world projects.

  • Data-Driven Insights and Analytics for Measurable Sustainable Development Goals

    • 1st Edition
    • Tilottama Goswami + 2 more
    • English
    Data-Driven Insights and Analytics for Measurable Sustainable Development Goals discusses the growing imperative to understand, measure, and guide actions using data-driven insights. The SDGs encompass a broad spectrum of global challenges, from eradicating poverty and hunger to preserving the environment and fostering peace. To address these issues, one should be able to measure and analyze progress. This book bridges the gap between qualitative and quantitative assessments, recognizing that goals are not solely about numbers but also encompass complex social, environmental, and economic dynamics. By merging data science with qualitative analysis, readers can explore how SDGs intersect and influence each other.The book provides readers with an understanding of how to effectively leverage data science models and algorithms using descriptive analytics, allowing us to assess the current state of SDG performance and offering valuable insights into where we stand on these critical goals. Prescriptive analytics guides actions by offering actionable recommendations, while predictive analytics anticipates future trends and challenges, helping us navigate our path toward the SDGs effectively.

  • Applied Graph Data Science

    Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases
    • 1st Edition
    • Pethuru Raj + 4 more
    • English
    Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.

  • Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications

    • 1st Edition
    • Siddhartha Bhattacharyya + 3 more
    • English
    Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on recent, up-to-date technologies, combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications.

  • Health Systems Science Education: Development and Implementation

    • 1st Edition
    • Volume 4
    • Rosalyn Maben-Feaster + 5 more
    • English
    **Selected for 2026 Doody's Core Titles in Medical Education**Now taught in a majority of medical schools nationwide, health systems science (HSS) prepares learners for the health systems of the future—an essential topic in modern health care. Health Systems Science Education, part of the American Medical Association’s MedEd Innovation Series, is a first-of-its-kind, instructor-focused field book that that equips educators to not just teach health systems science, but to know how to integrate and implement HSS comprehensively and effectively across the curriculum. This change management-oriented volume.

  • Meeting the Challenges of Data Quality Management

    • 1st Edition
    • Laura Sebastian-Coleman
    • English
    Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges. The book enables data management professionals to help their organizations get more value from data by addressing the five challenges of data quality management: the meaning challenge (recognizing how data represents reality), the process/quality challenge (creating high-quality data by design), the people challenge (building data literacy), the technical challenge (enabling organizational data to be accessed and used, as well as protected), and the accountability challenge (ensuring organizational leadership treats data as an asset). Organizations that fail to meet these challenges get less value from their data than organizations that address them directly. The book describes core data quality management capabilities and introduces new and experienced DQ practitioners to practical techniques for getting value from activities such as data profiling, DQ monitoring and DQ reporting. It extends these ideas to the management of data quality within big data environments. This book will appeal to data quality and data management professionals, especially those involved with data governance, across a wide range of industries, as well as academic and government organizations. Readership extends to people higher up the organizational ladder (chief data officers, data strategists, analytics leaders) and in different parts of the organization (finance professionals, operations managers, IT leaders) who want to leverage their data and their organizational capabilities (people, processes, technology) to drive value and gain competitive advantage. This will be a key reference for graduate students in computer science programs which normally have a limited focus on the data itself and where data quality management is an often-overlooked aspect of data management courses.

  • Intelligent Data Security Solutions for e-Health Applications

    • 1st Edition
    • Amit Kumar Singh + 1 more
    • English
    E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications. Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications.

  • Data Governance

    How to Design, Deploy, and Sustain an Effective Data Governance Program
    • 2nd Edition
    • John Ladley
    • English
    Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program.

  • Mosby's Dental Dictionary

    • 4th Edition
    • Elsevier Inc
    • English
    **Selected for Doody’s Core Titles® 2024 with "Essential Purchase" designation in Dictionaries/Termino... essential dental resource that goes beyond education! Mosby's Dental Dictionary, 4th Edition is the must-have, pocket-sized reference covering all areas of dentistry that’s designed for both students and practitioners. This new edition defines over 10,000 terms on dynamic areas of dentistry, including materials, imaging, surgery, orthodontics, pain control, and more.　Throughout the text, over 300 illustrations address new innovations, research, technology, and products in the field, and extensive appendices provide quick access to the information you will use every day. Plus, a free companion website contains more than 5,000 audio pronunciations, 500 additional images, videos, and animations to help illustrate key concepts.

  • Examen clinique et sémiologie - Macleod

    Interrogatoire et examen clinique - Sémiologie par appareil - Situations particulières
    • 1st Edition
    • J. Alastair Innes + 3 more
    • French
    L’examen clinique est essentiel à l’identification d’une maladie et l’évaluation de son pronostic.Cet ouvrage de référence dans le monde médical anglo-saxon explique avec détail comment évaluer les symptômes d’un patient et établir un diagnostic au travers de l’anamnèse et de l’examen physique.Son objectif est d’aider l’étudiant à développer les compétences cliniques nécessaires à l’obtention d’une anamnèse claire et les compétences pratiques indispensables à la détection et l’interprétation des signes cliniques des maladies.Le livre est composé de quatre grandes parties :Anamnèse et examen physique : elle aborde les principes généraux d’une bonne interaction avec le patient, depuis les bases du recueil de l’anamnèse et de la réalisation d’un examen physique à l’utilisation de tableaux cliniques permettant des diagnostics.Sémiolog... par appareil : cette partie traite des symptômes et des signes selon une approche par système.Situations spécifiques : elle illustre l’application de ces compétences à des situations cliniques particulières.Mise en pratique : cette partie s’intéresse à l’application de ces compétences à la pratique quotidienne et propose des conseils pour s’y préparer efficacement.Il est également proposé dans chaque chapitre des exemples d’Examen Clinique Objectif Structuré correspondant à une méthode d’évaluation des étudiants très prisée dans les pays anglo-saxons. Ils consistent en une mise en situation pratique face à un mannequin ou un comédien jouant un scénario clinique court.Ce livre aborde également les différentes étapes de chaque examen qui sont présentées de manière détaillée, étayées de nombreux encadrés et illustrations. Il est particulièrement adapté aux étudiants en DFGSM2-DFGSM3 dans le cadre de l’enseignement thématique « Sémiologie générale » et les enseignements intégrés par système (sémiologie clinique) mais également aux étudiants en pharmacie. Il intéressera également les étudiants en DFASM préparant les ECNi mais aussi les enseignants et praticiens désireux de mettre à jour leurs connaissances.

  • Rodak's Hematology

    Clinical Principles and Applications
    • 6th Edition
    • Elaine M. Keohane + 2 more
    • English
    **Selected for Doody’s Core Titles® 2024 in Laboratory Technology**Make sure you are thoroughly prepared to work in a clinical lab. Rodak’s Hematology: Clinical Principles and Applications, 6th Edition uses hundreds of full-color photomicrographs to help you understand the essentials of hematology. This new edition shows how to accurately identify cells, simplifies hemostasis and thrombosis concepts, and covers normal hematopoiesis through diseases of erythroid, myeloid, lymphoid, and megakaryocytic origins. Easy to follow and understand, this book also covers key topics including: working in a hematology lab; complementary testing areas such as flow cytometry, cytogenetics, and molecular diagnostics; the parts and functions of the cell; and laboratory testing of blood cells and body fluid cells.

  • Data Science

    Concepts and Practice
    • 2nd Edition
    • Vijay Kotu + 1 more
    • English
    Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You’ll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more...

  • PROP - Module H: Health Insurance Basics, Claims Processing and Computerized Billing Elsevier eBook on VitalSource

    • 4th Edition
    • Zenith
    • English

  • PROP - Module G: Nervous System, Law and Ethics, Psychology and Therapeutic Procedures Elsevier eBook on VitalSource

    • 4th Edition
    • Zenith
    • English

  • PROP - Module F: Pediatrics, Geriatrics, Endocrine and Reproductive Systems Elsevier eBook on VitalSource

    • 4th Edition
    • Zenith
    • English

  • PROP - Module B: Skeletal and Muscular System, Infection Control, Minor Office Surgery and Pharmacology Elsevier eBook on VitalSource

    • 4th Edition
    • Zenith
    • English

  • PROP - Module A: Integumentary, Sensory Systems, Patient Care and Communication Elsevier eBook on VitalSource

    • 4th Edition
    • Zenith
    • English

  • Misch's Avoiding Complications in Oral Implantology

    • 1st Edition
    • Carl E. Misch + 1 more
    • English
    See how to effectively manage ALL dental implant complications throughout ALL phases of treatment! Avoiding Complications in Oral Implantology provides evidence-based management protocols for a wide range of implant problems such as placement complications, malpositioning, bleeding, infection, and nerve injuries. Hundreds of high-quality, full-color photos and illustrations clearly demonstrate the complications and their resolution. Edited by Carl Misch and Randolph Resnik — both well-known names in dental implantology and prosthodontics — and with a team of expert contributors, this authoritative guide helps you handle the implant-related complications that can occur as more and more patients choose dental implants.

  • How Nursing has Changed with Technology, An Issue of Nursing Clinics

    • 1st Edition
    • Volume 50-2
    • Maria Overstreet
    • English
    How has technology changed the art and science of nursing practice?Many facets of nursing practice have stayed constant over the years such as the way we advocate for our patients and the art of caring for our patients. However, nursing practice has evolved over the years especially in the bedside delivery of state of the art nursing care. Technology at the bedside has forced nurse educators to change the ways in which we always have taught nursing students. Technology has also begun to change the methods used in the actual bedside nursing care. In this issue, you will hear from some of the nursing experts in areas of nursing care that has changed in either the delivery of care or method of assessing care of the patient. Nursing experts will describe some of the historical changes and intrigue you in the changes expected to come to the bedside. Why is this issue important? First, we gain insight from a review of where we have been and nurses tend to reminisce on our past as well as romance our historical roots. Second, technology is ever changing and it is good practice to keep abreast of what is happening in other areas of nursing so that we can apply others successes in our own specific areas of nursing. Third, informatics in nursing is a growing field and nursing must embrace technology and learn to adapt various methods of delivery so that we can appropriately care for and advocate for our patients.With the changes in our national healthcare system, we must encourage nurses to try out new methods of delivery as well as encourage their ideas of how nursing can change. The articles in this issue reflect these changes.

  • Geriatric Dentistry, An Issue of Dental Clinics of North America

    • 1st Edition
    • Volume 58-4
    • Lisa A. Thompson
    • English
    This issue of Dental Clinics, edited by Lisa A. Thompson and Leonard J. Brennan, focuses on Geriatric Dentistry. Articles include: Our Current Geriatric Population: Demographic and Oral Health Care Utilization; Physiology of Aging of Older Adults: Systemic and Oral Health Considerations; Treatment Planning Considerations in Older Adults; Oral Health Disparity in Older Adults: Dental Decay and Tooth Loss; Oral Health Disparities in Older Adults: Oral bacteria, Inflammation and Aspiration Pneumonia; Salivary Function and Xerostomia and the Implications of Polypharmacy in Elderly; Systemic and Oral Health; Cognitive Impairment in Older Adults and Oral Health considerations: Treatment and Management; Integrating Oral Health into the Interdisciplinary Health Sciences Curriculum; Innovations in Dental Care Delivery for the Older Adult; and more!

  • Data Acquisition Techniques Using PC

    • 1st Edition
    • Howard Austerlitz
    • English
    Data Acquisition Techniques Using Personal Computers contains all the information required by a technical professional (engineer, scientist, technician) to implement a PC-based acquisition system. Including both basic tutorial information as well as some advanced topics, this work is suitable as a reference book for engineers or as a supplemental text for engineering students. It gives the reader enough understanding of the topics to implement a data acquisition system based on commercial products. A reader can alternatively learn how to custom build hardware or write his or her own software. Featuring diverse information, this book will be useful to both the technical professional and the hobbyist.

  • Archives and the computer

    • 2nd Edition
    • Michael J. Cook
    • English
    Archives and the Computer deals with the use of the computer and its systems and programs in archiving data and other related materials. The book covers topics such as the scope of automated systems in archives; systems for records management, archival description, and retrieval; and machine-readable archives. The selection also features examples of archives from different institutions such as the University of Liverpool, Berkshire County Record Office, and the National Maritime Museum.The text is recommended for archivists who would like to know more about the use of computers in archiving of records and other related information.

  • Measuring Data Quality for Ongoing Improvement

    A Data Quality Assessment Framework
    • 1st Edition
    • Laura Sebastian-Coleman
    • English
    The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You’ll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies.

  • PDA Bundle (Online) - GIW Gahart 2012, Ignatavicius Clinical Companion & Stillwell Critical Care Nursing Reference

    • 1st Edition
    • Mosby
    • English