AI-driven Innovations in Physiotherapy and Oncology, Volume 2

Abhishek Kumar, Senior IEEE Member and Professor at Chandigarh University, India, is a prolific researcher with 170+ publications and has international postdoctoral experience. His expertise spans AI, renewable energy and image processing.Priya Batta is Associate Professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her expertise includes AI, blockchain and IoT.Sachin Ahuja is Executive Director of Engineering and Professor at Chandigarh University, India. He has guided numerous ME and PhD scholars and currently specializes in AI, machine learning, data mining and related areas.Pramod Singh Rathore, Assistant Professor at Manipal University Jaipur, India, has over 12 years of experience and 85+ publications. His research interests include NS2, networks, data mining, DBMS and professional memberships including ACM and IAENG.

• Preface xixAbhishek KUMAR, Priya BATTA, Sachin AHUJA and Pramod Singh RATHOREChapter 1. Advancements and Applications of Physiotherapy in Rehabilitation and Pain Management 1G. HIMASHREE, G. VARADHARAJULU and Radhika CHINTAMANI1.1. Introduction 21.2. Composition of connective tissue 31.3. Tendon classification 51.4. Tendon vascularity. 61.5. Tendinous junction 101.6. Mechanical properties 131.7. Viscoelastic behavior of tendons to tensile loads 271.8. Biomechanical response of tendons to nontensile loads 331.9. Impact of physical environment on mechanical properties 341.10. Biological effects on mechanical properties 351.11. Tendon injury mechanism 361.12. Response of tendons to immobilization and mobilization 431.13. Conclusion 441.14. References 44Chapter 2. Model Validation Techniques for AI in Cancer Research Based on Physiotherapy and Oncology 49Shraddha MOHITE, Suresh J. BHOSALE, Salim CHAVAN and Kadam SHRIKANT2.1. Introduction 502.2. Role of AI in oncology and physiotherapy 502.3. AI model development pipeline in cancer research 522.4. Validation techniques 572.5. Key metrics for model evaluation 602.6. Challenges in validation for cancer physiotherapy models 632.7. Regulatory and ethical considerations 652.8. Future directions 672.9. Conclusion 672.10. References 68Chapter 3. The Role of Artificial Intelligence in Personalized Physiotherapy and Cancer Treatment 73S. ANANDH, Suresh J. BHOSALE and Sachin Purushottam UNTAWALE3.1. Introduction 733.2. Overview of AI in healthcare 753.3. Personalized physiotherapy 783.4. Personalized cancer treatment 793.5. Challenges and ethical considerations 823.6. Prospects 833.7. Conclusion 843.8. References 85Chapter 4. Machine Learning in Oncology and Physiotherapy: A New Era of Precision Medicine 89Mandar MALAWADE, Shrushti P. JACHAK, Anand GUDUR and Sanjay L. BADJAT4.1. Introduction 894.2. Machine learning in oncology 914.3. Machine learning in physiotherapy 944.4. Challenges and limitations 984.5. Future directions 994.6. Conclusion 1004.7. References 101Chapter 5. The Role of Physiotherapy in Enhancing Functional Recovery: Techniques, Benefits and Clinical Perspectives 105Radhika CHINTAMANI, G. VARADHARAJULU and G. HIMASHREE5.1. Introduction 1065.2. Neural tissue mechanics 1085.3. Material properties 1135.4. Quasi-linear viscoelasticity 1155.5. Load-deformation curve 1185.6. Conclusion 1225.7. References 123Chapter 6. AI-Powered Rehabilitation: Transforming Physiotherapy for Cancer Survivors 127Namrata KADAM, Suresh J. BHOSALE and Piyush Ashokrao DALKE6.1. Introduction 1286.2. The burden of cancer survivorship 1296.3. AI in healthcare and rehabilitation 1316.4. Personalized rehabilitation for cancer survivors 1326.5. Remote monitoring and tele-rehabilitation 1336.6. Enhancing patient engagement and motivation 1346.7. Clinical outcomes and evidence-based practice 1356.8. Challenges and ethical considerations 1376.9. Future directions and recommendations 1376.10. Conclusion 1386.11. References 139Chapter 7. Future Directions in Oncology: Emerging Technologies and Artificial Intelligence in Physiotherapy 143Chandrakant PATIL, Dhiraj Kumar MANE, Anand GUDUR and Kalpana MALPE7.1. Introduction 1447.2. Emerging technologies in oncology physiotherapy 1457.3. AI in oncology physiotherapy 1507.4. Integration of technologies and AI in clinical practice 1517.5. Challenges and ethical considerations 1547.6. Future directions 1557.7. Conclusion 1567.8. References 157Chapter 8. Deep Learning in Oncology and Physiotherapy: Enhancing Diagnosis and Recovery 161Poonam PATIL, Neeraja ASWALE, Dhiraj Kumar MANE and Anand GUDUR8.1. Introduction 1618.2. DL fundamentals 1628.3. DL applications in oncology 1648.4. DL applications in physiotherapy 1678.5. Challenges and limitations 1708.6. Case studies 1728.7. Future directions 1738.8. Conclusion 1738.9. References 174Chapter 9. Automating Cancer Detection and Rehabilitation: The AI Revolution 179Suraj KANASE, Rashmi GUDUR and Rasika MANAPU9.1. Introduction 1809.2. AI in cancer detection 1829.3. Predictive analytics and risk assessment 1859.4. Personalized treatment planning 1879.5. AI in cancer rehabilitation 1899.6. Challenges and ethical considerations 1919.7. Case studies and clinical applications 1929.8. Future directions 1939.9. Conclusion 1939.10. References 194Chapter 10. Physiotherapy: A Holistic Approach to Rehabilitation and Functional Wellness 199G. HIMASHREE, Radhika CHINTAMANI and G. VARADHARAJULU10.1. Introduction 19910.2. AI in biomaterials 20110.3. History 20110.4. Biomaterials: properties, types and applications 20210.5. Metals 20510.6. Ceramics and glasses 21010.7. Polymers 21310.8. Natural materials and composites 21510.9. Conclusion 21610.10. References 216Chapter 11. AI and Wearable Technology in Physiotherapy for Oncology Patients 221Trupti YADAV, Anand GUDUR and Vibha VYAS11.1. Introduction 22211.2. Background and motivation 22411.3. Wearable technology in oncology physiotherapy 22611.4. AI in oncology physiotherapy 22711.5. Case studies and clinical trials 22911.6. Benefits and clinical impact 23111.7. Challenges and limitations 23211.8. Future directions 23411.9. Conclusion 23511.10. References 236Chapter 12. Smart Robotics in Physiotherapy and Oncology: Redefining Patient Outcomes 239Pragati SALUNKHE, Suresh J. BHOSALE and Prashant S. JADHAV12.1. Introduction 24012.2. Background and technological foundations 24112.3. Smart robotics in physiotherapy 24312.4. Smart robotics in oncology 24612.5. Integration with AI 24812.6. Challenges and limitations 25212.7. Future directions 25312.8. Conclusion 25312.9. References 254Chapter 13. Recurrent Neural Networks for Predictive Modeling in Cancer Time Series Data 257Mayiri BURUNGALE, Suresh J. BHOSALE, Rashmi GUDUR and Shamla MANTRI13.1. Introduction 25713.2. Background and related work 25813.3. RNN architectures 26013.4. Datasets and preprocessing 26313.5. Applications in cancer prediction 26713.6. Evaluation metrics 26813.7. Challenges and limitations 26913.8. Future directions 26913.9. Conclusion 27113.10. References 271Chapter 14. The Role of Physiotherapy in Enhancing Functional Recovery in Musculoskeletal and Neurological Conditions 275G. VARADHARAJULU, Radhika CHINTAMANI and G. HIMASHREE14.1. Introduction 27614.2. Hierarchical structure of cortical bone 27714.3. Psychological support 28514.4. Application of artificial intelligence (AI) in tissue regeneration 28514.5. Conclusion 28814.6. References 288Chapter 15. Biomechanics in Physiotherapy 291Sougata PANDA and Seveka BALI15.1. Introduction 29115.2. Methodology 29415.3. Literature review 29415.4. Results 30415.5. Discussion. 30515.6. Conclusion 30615.7. References 306Chapter 16. Role of Physiotherapy in Cancer Recovery: A Review and Recommendation 317Sougata PANDA16.1. Introduction 31716.2. Literature review 31916.3. Methods 32216.4. Result 32216.5. Discussion. 32716.6. Recommendations 32716.7. Conclusion 32816.8. References 328Chapter 17. The Role of Artificial Intelligence in Modern Healthcare: Transforming Diagnosis, Treatment and Rehabilitation 335Mamta17.1. Introduction to artificial intelligence (AI) in healthcare 33517.2. Literature review 33717.3. Methodology 34017.4. How AI is disrupting healthcare today 34217.5. Applications of AI across medical domains 34317.6. Benefits of AI in healthcare 34617.7. Challenges and ethical issues 34817.8. The future of AI in healthcare 35117.9. Conclusion 35417.10. References 355Chapter 18. Foundation of Artificial Intelligence in Healthcare 359RUCHI, BAANI, Vikas WASSON and Kamini JOSHI18.1. Introduction 36018.2. Overview of AI 36218.3. AI applications in medicine: literature review 36518.4. AI-based healthcare: methodologies 37018.5. Conclusion and future scope 37818.6. References 379List of Authors 385Index 389Summary of Volume 1 391