Medical Minds and Machine Learning

Transforming Care with AI

Sandeep Kumar Mathivanan, Saurav Mallik, Basu Dev Shivahare, Sangeetha S.K.B., Shakila Basheer

• Publisher: CRC Press
• Year: 2026
• Print ISBN:
  9781041212867
• Edition: 1
• eBook ISBN:
  9781040983188
• Topic: Technology & Engineering
• Subtopic: Robotics
• Index: Technology & Engineering

This volume reviews the convergence of AI and medicine. As healthcare systems face rising demands, clinician shortages, and the complexity of patient data, machine learning and deep learning are stepping in as transformative forces—to improve diagnosis, personalize treatments, and enhance patient outcomes. This book is a comprehensive guide to technologies, applications, and implications of AI in healthcare. It navigates through the foundational principles of machine learning, dives into real-world implementations such as radiology diagnostics, robotic surgery, and predictive analytics, and addresses key topics like natural language processing of EHRs and AI assisted drug discovery.

Key Features:

• Explores how generative AI is revolutionizing diagnostics in fields like radiology, oncology, and pathology, enhancing accuracy and efficiency in patient care.
• Addresses Ethical, Legal, and Regulatory Considerations.
• Bridges the Gap Between Technology and Clinical Practice.
• Highlights Future Trends and Innovations.
• Fosters Multidisciplinary Collaboration.

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Preface
• Contents
• Chapter 1 OptiCareNet: An Optimization-Driven AI Framework for Intelligent Clinical Decision Support
• Chapter 2 Adaptive Multimodal Diagnostic Network: A Hybrid Cross-Attention Approach for Explainable Clinical AI
• Chapter 3 CCRET: A Contextualized Clinical Representation Extraction Transformer for Advanced NLP in Electronic Health Records
• Chapter 4 AI-Driven Early Disease Detection and Risk Stratification using Multi-Omics Data Integration
• Chapter 5 AI-Enhanced Cardiac Risk Prediction and Early Diagnosis using Multi-Modal Imaging and Clinical Data
• Chapter 6 PAI-MED: A Personalized AI-Driven Medicine Framework Integrating Multi-Sensor Wearables for Predictive Healthcare
• Chapter 7 AI-Augmented Wearables and Remote Monitoring for Scalable Personalized Medicine: A Clinical and Economic Perspective
• Chapter 8 GEN-DRUG: A Generative AI-Driven Framework for Accelerated De Novo Drug Discovery and Lead Optimization
• Chapter 9 ETHIC-AID: A Framework for Ethical AI Deployment in Healthcare with Bias Mitigation, Transparency, and Accountability Controls
• Chapter 10 Federated Multimodal NLP for Privacy-Preserving Symptom Monitoring and Care Guidance
• Chapter 11 Auto-IntelliDx: A Self-Evolving Deep Learning Framework for Adaptive and Interpretable Clinical Diagnosis
• Chapter 12 A Self-Supervised Representation Learning Framework for Scalable Edge AI Deployment in Clinical Settings
• Chapter 13 AIMedMind: A Federated Deep Learning Framework for Real-Time Glycemic Forecasting and Adaptive Insulin Dosing
• Chapter 14 HEAL-Net: A Multimodal Deep Ensemble Framework for Enhanced Risk Prediction in Global Healthcare
• Chapter 15 MedBotX: An AI-Integrated Conversational System for Preliminary Medical Assistance
• Chapter 16 A Chatbot Service for Suicide Detection and Prevention
• Chapter 17 DeepSkinNet++: A Novel Feature Enrichment Framework for Advanced Dermatological Disease Classification Using Multiscale Spatio-Spectral Embeddings
• Chapter 18 AI-HyMedNet: A Hybrid Multimodal Deep Learning Network for Precision Medicine and Real-Time Disease Prediction
• Chapter 19 Quantum-Enhanced AI for Genomic Medicine: Accelerating Drug Discovery and Personalized Treatment through Hybrid Quantum-Classical Models
• Chapter 20 AI-Driven Digital Twin Framework for Predictive Healthcare: Integrating Real-Time EHR Data with Virtual Patient Simulations
• Chapter 21 Integration of Multimodal NLP Systems for Real-Time Clinical Decision Support in Digital Healthcare
• Index
• About the Editors