Generative Artificial Intelligence for Biomedical and Smart Health Informatics

Aditya Khamparia, Deepak Gupta

• Publisher: Wiley-IEEE Press
• Year: 2024
• Print ISBN: 9781394280704
• eBook ISBN: 9781394280728
• Edition: 1
• Topic: Medicine
• Subtopic: Artificial Intelligence (AI) & Semantics

Enables readers to understand the future of medical applications with generative AI and related applications

Generative Artificial Intelligence for Biomedical and Smart Health Informatics delivers a comprehensive overview of the most recent generative AI-driven medical applications based on deep learning and machine learning in which biomedical data is gathered, processed, and analyzed using data augmentation techniques. This book covers many applications of generative models for medical image data, including volumetric medical image segmentation, data augmentation, MRI reconstruction, and modeling of spatiotemporal medical data.

The book explores findings obtained by explainable AI techniques, with coverage of various techniques rarely reported in literature. Throughout, feedback and user experiences from physicians and medical staff, as well as use cases, are included to provide important context.

The book discusses topics including privacy and security challenges in AI-enabled health informatics, biosensor-guided AI interventions in personalized medicine, regulatory frameworks and guidelines for AI-based medical devices, education and training for building responsible AI solutions in healthcare, and challenges and opportunities in integrating generative AI with wearable devices.

Topics covered include:

• Treatment of neurological disorders using intelligent techniques and image-guided and tomography interventions for neuromuscular disorders
• Bio-inspired smart healthcare service frameworks with AI, machine learning, and deep learning, integration of IoT devices, and edge computing in industrial and clinical systems
• Traffic management and optimization in distributed environments, patient data management, disease surveillance and prediction, and telemedicine and remote monitoring
• Education-driven, peer-to-peer, and service-oriented architectures and transparency and accountability in medical decision-making

Generative Artificial Intelligence for Biomedical and Smart Health Informatics is an essential reference for computer science researchers, medical professionals, healthcare informatics, and medical imaging researchers interested in understanding the potential of artificial intelligence and other related technologies in healthcare.

Table of contents

• Cover
• Title Page
• Copyright
• Contents
• About the Editors
• List of Contributors
• Preface
• Acknowledgments
• Chapter 1 Generative AI in Wearables: Exploring the Impact of GANs, VAEs, and Transformers*
• Chapter 2 Safeguarding Privacy and Security in AI‐Enabled Healthcare Informatics
• Chapter 3 Generating Synthetic Medical Data Using GAI
• Chapter 4 Automation of Drug Design and Development
• Chapter 5 Autism Spectrum Disorder Diagnosis: A Comprehensive Review of Machine Learning Approaches
• Chapter 6 Temporal Normalization and Brain Image Analysis for Early‐Stage Prediction of Attention Deficit Hyperactivity Disorder (ADHD)
• Chapter 7 Sustainable Agriculture Through Advanced Crop Management: VGG16‐Based Tea Leaf Disease Recognition
• Chapter 8 Advancing Colorectal Cancer Diagnosis: Integrating Synthetic Data and Machine Learning for Microbiome Analysis
• Chapter 9 Recent Knowledge in Drug Design and Development: Automation and Advancement
• Chapter 10 Machine Learning and Generative AI Techniques for Sentiment Analysis with Applications
• Chapter 11 Use of AI with Optimization Techniques: Case Study, Challenges, and Future Trends
• Chapter 12 Inclusive Role of Internet of (Healthcare) Things in Digital Health: Challenges, Methods, and Future Directions
• Chapter 13 Generating Synthetic Medical Dataset Using Generative AI: A Case Study
• Chapter 14 A Comprehensive Review of Cardiac Image Analysis for Precise Heart Disease Diagnosis Using Deep Learning Techniques
• Chapter 15 Classification Methods of Deep Learning for Detecting Autism Spectrum Disorder in Children (4–12 Years)
• Chapter 16 Deep Learning Model for Resolution Enhancement of Biomedical Images for Biometrics
• Chapter 17 Tackling the Complexities of Federated Learning
• Chapter 18 Revolutionizing Healthcare: The Impact of AI‐Powered Sensors
• Chapter 19 GAI and Deep Learning‐Based Medical Sensor Data Relationship Model for Health Informatics
• Chapter 20 Leveraging Generative Adversarial Networks for Image Augmentation in Deep Learning
• Chapter 21 Exploring Trust and Mistrust Dynamics: Generative AI‐Curated Narratives in Health Communication Media Content Among Gen X
• Chapter 22 Generative Intelligence‐Based Federated Learning Model for Brain Tumor Classification in Smart Health
• Chapter 23 AI‐Based Emotion Detection System in Healthcare for Patient
• Chapter 24 Leveraging Process Mining for Enhanced Efficiency and Precision in Healthcare
• Chapter 25 Transform Drug Discovery and Development With Generative Artificial Intelligence
• Chapter 26 Medical Image Analysis and Morphology with Generative Artificial Intelligence for Biomedical and Smart Health Informatics
• Chapter 27 Machine Learning Applications in the Prediction of Polycystic Ovarian Syndrome
• Chapter 28 Diagnosis and Classification of Skin Cancer Using Generative Artificial Intelligence (Gen AI)
• Chapter 29 Secure Decentralized ECG Prediction: Balancing Privacy, Performance, and Heterogeneity
• Index
• EULA