AI-driven Innovations in Physiotherapy and Oncology 3

Abhishek Kumar, Priya Batta, Sachin Ahuja, Pramod Singh Rathore

• Publisher: Wiley-ISTE
• Year: 2026
• Print ISBN:
  9781836690887
• Edition: 1
• eBook ISBN:
  9781394452217
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

AI-driven Innovations in Physiotherapy and Oncology 3 is positioned at the intersection of artificial intelligence (AI), clinical rehabilitation and cancer care, addressing the growing need for data-driven, personalized and technology-enabled healthcare solutions. The book contextualizes recent advances in machine learning, deep learning, computer vision and intelligent decision-support systems within modern physiotherapy and oncology practices.

This book systematically explores how AI models enhance diagnosis, treatment planning, therapy optimization and outcome prediction across musculoskeletal rehabilitation, neuro-physiotherapy, radiation oncology and precision cancer care. It covers sensor-based motion analysis, AI-assisted imaging, predictive analytics, digital therapeutics and intelligent rehabilitation platforms, supported by real-world case studies and implementation frameworks. The book also discusses ethical considerations, clinical validation, interoperability and regulatory challenges to bridge the gap between research and practice. Designed for researchers, clinicians, graduate students and healthcare technologists, this book provides both theoretical foundations and practical insights for integrating AI into next-generation physiotherapy and oncology workflows

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright Page
• Preface
• 1 Reinforcement Learning Models for Adaptive Cancer Rehabilitation in Physiotherapy
• 2 AI-Enabled Gait and Balance Assessment in Oncology Rehabilitation
• 3 Deep Learning-Driven Fatigue Monitoring in Cancer Physiotherapy Programs
• 4 Predictive Modeling of Lymphedema Risk Using AI in Oncology Physiotherapy
• 5 AI-Based Movement Quality Scoring for Post-Chemotherapy Rehabilitation
• 6 Virtual Reality and AI for Pain Management in Cancer Physiotherapy
• 7 Machine Learning for Optimizing Exercise Intensity in Oncology Rehabilitation
• 8 AI-Driven Digital Twins for Simulating Physiotherapy Outcomes in Cancer Care
• 9 Natural Language Processing of Patient Feedback to Personalize Oncology Physiotherapy
• 10 AI-Enhanced Biomechanical Feedback Systems for Radiation Therapy Recovery
• 11 Computer Vision for Real-time Postural Correction in Cancer Physiotherapy
• 12 AI-Driven Remote Physiotherapy Platforms for Immunocompromised Cancer Patients
• 13 Machine Learning for Early Detection of Mobility Decline in Oncology Patients
• 14 Predictive Analytics for Return-to-Function Timelines in Cancer Survivors
• 15 AI-Enabled Monitoring of Neuromuscular Recovery in Cancer Rehabilitation
• 16 Automated Motion Capture Systems for Oncology Physiotherapy Using AI
• 17 Machine Learning to Forecast Rehabilitation Needs After Oncological Surgery
• 18 AI-Driven Wearable Sensors for Personalized Cancer Recovery Programs
• 19 Computer Vision-Based Range of Motion Analysis in Oncology Physiotherapy
• 20 AI-Powered Robotic Assistance for Cancer Patient Physiotherapy
• List of Authors
• Index
• Other titles from iSTE in Computer Engineering
• End User License Agreement