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Books in Biotechnology

Exploring genetic engineering, cell culture, and bioprocessing, this collection supports researchers and industry professionals developing new therapies, diagnostics, and sustainable bio products. It features innovative techniques, case studies, and regulatory considerations, enabling advancements in healthcare, agriculture, and environmental solutions within a rapidly evolving biotech landscape.

  • Artificial Intelligence Applications in Emerging Healthcare Technologies

    • 1st Edition
    • Miguel Antonio Wister Ovando + 2 more
    • English
    Artificial Intelligence Applications in Emerging Healthcare Technologies presents the latest advances and state-of-the-art methods and applications of computer science and emerging AI technologies in health and medicine. It explores the impact of artificial intelligence (AI) in healthcare for medical decision-making and data analysis, tackling topics such as cloud computing, cybersecurity, the internet of things, natural language processing, virtual health, data science applied to healthcare, personalized medicine, imaging, diagnosis, drug discovery, and diseases, among others. It is a great resource for researchers and students to learn how machine learning algorithms and other data science techniques have been implemented to solve healthcare-related problems. Chapters present adaptations or improvements on previous models and algorithms to process data from different sources. Other chapters investigate new formulations for the optimization of known procedures and algorithms. Finally, all chapters use experimental methods to study problems of interest in healthcare.

  • Advanced MR Techniques for Neurodegenerative Diseases

    • 1st Edition
    • Volume 13
    • Kannie Wy Chan + 3 more
    • English
    Advanced MR Techniques for Neurodegenerative Diseases covers state of the art developments in physiologic, metabolic, functional, and microstructural MRI of the brain. It provides an overview of these approaches and includes dynamic contrast enhanced (DCE) MRI, dynamic susceptibility contrast (DSC) MRI, arterial spin labeling (ASL), chemical exchange saturation transfer (CEST) MRI, magnetic resonance spectroscopy (MRS), resting state functional MRI (rsfMRI), microscopic diffusion imaging, and quantitative susceptibility mapping (QSM). Chapters then follow that present the application of these methods to Alzheimer’s Disease and vascular dementia, small vessel disease, Parkinson’s Disease, Lewy body dementia, Huntington’s Disease, Amyotrophic Lateral Sclerosis, and Multiple Sclerosis.Advanced MR Techniques for Neurodegenerative Diseases is a comprehensive resource on the latest advanced MR techniques and their application to neurodegenerative diseases, suitable for MR engineers and physicists as well as clinicians and neuroscientists who use MR techniques for diagnosis and research.

  • Deep Learning Assessment of Neurological Imaging

    • 1st Edition
    • Tripti Goel + 3 more
    • English
    Deep Learning Assessment of Neurological Imaging provides an introduction to deep learning structures and pre-processing methods for detecting MRI anomalies. It also provides a comprehensive account of deep learning research on MRI images for Alzheimer's disease, Parkinson's disease, and schizophrenia, and a discussion on current research issues and future objectives. The book is a valuable resource to guide new entrants in the field to make a meaningful impact in their development efforts. The book concludes with a brief overview of the problems discussed and potential future advancements in the field.

  • Advances in Applied Microbiology

    • 1st Edition
    • Volume 134
    • English
    Advances in Applied Microbiology, Volume 134 presents a comprehensive exploration of the latest innovations in applied microbiology. The book delves into the diverse applications of microbiology across various industries, including agriculture, food production, biotechnology, environmental science, and healthcare. Through a collection of insightful chapters authored by experts in the field, readers are offered in-depth analyses of cutting-edge research, emerging trends, and practical applications of microbiological principles.From novel microbial technologies to the impact of microbiomes on human health and beyond, this book serves as a valuable resource for researchers, professionals, and students seeking to stay informed and inspired by the exciting advancements.

  • Intelligent Cyber-Physical Systems for Sustainable Healthcare

    • 1st Edition
    • Vandana Bajaj + 5 more
    • English
    Intelligent Cyber-Physical Systems for Sustainable Healthcare addresses the integration of emerging technologies like Virtual Reality, Smart Robotics, and Human-Computer Interaction, which are crucial for maximizing digital health's potential. The book includes case studies that highlight challenges faced by medical practitioners and industry professionals, providing valuable insights for designing sustainable iCPS solutions. Aimed at biomedical engineers, researchers, and industry professionals, it offers guidance for developing practical applications in sustainable healthcare. Additionally, shared, cross-disciplinary experiences assist engineers with less clinical expertise in enhancing healthcare applications in the intelligent digital health sector. Overall, case studies illustrate past challenges in the healthcare industry and present effective solutions to overcome them, making the book a comprehensive resource for advancing sustainable healthcare practices.

  • Non-stationary and Nonlinear Data Processing for Automated Computer-Aided Medical Diagnosis

    • 1st Edition
    • Rajesh Kumar Tripathy + 3 more
    • English
    Non-Stationary and Nonlinear Data Processing for Automated Computer-Aided Medical Diagnosis demonstrates the applications of machine learning and deep learning combined with signal processing techniques for human-machine interface applications using EMG signals. The book includes the analysis and classification of various heart diseases based on bio-signals like electrocardiogram (ECG), photoplethysmography (PPG), and phonocardiogram (PCG) signals. Various machine learning approaches, including advanced algorithms like multivariate signal processing, time-frequency analysis, and nonlinear signal processing are covered for CAD of neural, muscular, and cardiovascular diseases. The methods for CAD of various brain disorders are also included. Presented techniques utilize advanced non-stationary and nonlinear signal processing, along with machine learning and deep learning-based classification processes. CAD methods for diagnosing various neurological diseases are based on bio-signals such as electroencephalogram (EEG) and magnetoencephalogram (MEG), as well as medical images like magnetic resonance imaging (MRI) and computerized tomography (CT). Finally, the book addresses various types of medical signals and images, integrating nonlinear and non-stationary signal processing, machine learning, and deep learning within the CAD framework for diagnosing various diseases.

  • Advances in Applied Microbiology

    • 1st Edition
    • Volume 133
    • English
    Advances in Applied Microbiology, Volume 133 presents a comprehensive exploration of the latest innovations in applied microbiology. The book delves into the diverse applications of microbiology across various industries, including agriculture, food production, biotechnology, environmental science, and healthcare. Through a collection of insightful chapters authored by experts in the field, readers are offered in-depth analyses of cutting-edge research, emerging trends, and practical applications of microbiological principles.From novel microbial technologies to the impact of microbiomes on human health and beyond, this book serves as a valuable resource for researchers, professionals, and students seeking to stay informed and inspired by the exciting advancements.

  • Metaverse and AI in Healthcare

    A Federated Learning Approach
    • 1st Edition
    • Jyotir Moy Chatterjee + 1 more
    • English
    Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. It fills a critical gap by exploring how federated learning enables secure, decentralized data sharing and personalized medicine in virtual health platforms, meeting urgent demands for privacy, interoperability, and innovation. The book is structured into four parts covering foundational AI and federated learning concepts, augmented reality and metaverse applications, legal and cybersecurity challenges, and emerging strategic trends. Contributors from academia and industry present chapters on predictive modeling, cybersecurity frameworks, AR fitness, legal perspectives, and AI-driven medical tourism, supported by case studies and technical explanations. This reference equips graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare with practical knowledge and forward-looking analysis. It empowers readers to navigate evolving digital health ecosystems, addressing data privacy, customized care, and global access challenges through federated learning and metaverse solutions.

  • Deep Learning Applications in Neuroinformatics

    Advances, Methods, and Perspectives
    • 1st Edition
    • Karthik Ramamurthy
    • English
    Deep Learning Applications in Neuroinformatics: Advances, Methods, and Perspectives explores how deep learning revolutionizes neuroinformatics, covering the latest methods and applications of deep learning in analyzing neuroimaging data from EEG, MRI, PET, and more. The book addresses critical neurological disorders like Alzheimer’s disease, Mild Cognitive Impairment, Stroke, and Autism Spectrum Disorder, bridging the gap between neuroscience and artificial intelligence. It is an ideal resource for researchers, practitioners, and students with insights from leading experts.

  • Deep Learning for Cardiac Signal Analysis in Robotic Applications

    • 1st Edition
    • Kapil Gupta + 1 more
    • English
    Deep Learning for Cardiac Signal Analysis in Robotic Applications delves into the transformative role of artificial intelligence in enhancing robotic-assisted cardiovascular procedures. Addressing the complexities of heart signal interpretation amidst the dynamic environment of cardiac surgery, this book meets the critical need for a comprehensive resource that bridges deep learning advances with practical surgical applications. It responds to the challenge of understanding intricate bio-signals, such as ECG, VCG, and BCG, by providing clear explanations, case studies, and methodological insights tailored to improve surgical precision, safety, and patient outcomes. The book is organized into three parts, starting with the fundamentals of cardiac signals and deep learning. It introduces key heart modalities, including the physiological underpinnings and challenges of signals like ECG and BCG, followed by an overview of deep learning architectures relevant to signal processing. Pre-processing and feature extraction techniques are detailed to prepare readers for advanced analysis. Part II focuses on AI-enhanced cardiac signal analysis, covering arrhythmia detection, myocardial ischemia diagnostics, hypertension monitoring via BCG, and explainable AI approaches for fetal arrhythmia monitoring. The final section integrates AI with robotic cardiac surgery, addressing real-time signal integration, AI-guided intervention precision, intraoperative decision support, postoperative monitoring, and future trends in cardiac AI and robotic-assisted surgery.This book is an invaluable resource for engineering students and academicians seeking to deepen their understanding of AI applications in healthcare. It equips readers with practical knowledge to tackle challenges in cardiac signal processing and robotic application, fostering interdisciplinary expertise that spans biomedical engineering, computer science, and clinical practice. This book not only advances academic research but also supports innovation in developing intelligent surgical systems and improving patient care.

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