AI-driven Innovations in Physiotherapy and Oncology, Volume 2
Description
AI-driven Innovations in Physiotherapy and Oncology 2 explores the transformative impact of artificial intelligence (AI) on two critical domains of healthcare. As the global demand for personalized, efficient and data-driven medical interventions increases, this book offers a timely examination of how AI technologies are reshaping clinical practices in both physiotherapy and oncology.
The book explores how AI supports early cancer detection, personalized treatment planning and monitoring of disease progression, while also playing a pivotal role in physiotherapy by enabling intelligent rehabilitation strategies tailored to oncology patients. From AI-driven motion analysis and virtual physiotherapy assistants to predictive models for treatment response and functional recovery, this book showcases innovations that optimize physical therapy outcomes for cancer patients. It also addresses ethical challenges, data governance and the integration of AI within clinical workflows. Designed for clinicians, researchers and healthcare innovators, this book is a vital resource for understanding how AI bridges the gap between oncology care and rehabilitative physiotherapy.
More details
Other editions
Additional editions
Persons
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.
Content
Preface xix
Abhishek KUMAR, Priya BATTA, Sachin AHUJA and Pramod Singh RATHORE
Chapter 1. Advancements and Applications of Physiotherapy in Rehabilitation and Pain Management 1
G. HIMASHREE, G. VARADHARAJULU and Radhika CHINTAMANI
1.1. Introduction 2
1.2. Composition of connective tissue 3
1.3. Tendon classification 5
1.4. Tendon vascularity. 6
1.5. Tendinous junction 10
1.6. Mechanical properties 13
1.7. Viscoelastic behavior of tendons to tensile loads 27
1.8. Biomechanical response of tendons to nontensile loads 33
1.9. Impact of physical environment on mechanical properties 34
1.10. Biological effects on mechanical properties 35
1.11. Tendon injury mechanism 36
1.12. Response of tendons to immobilization and mobilization 43
1.13. Conclusion 44
1.14. References 44
Chapter 2. Model Validation Techniques for AI in Cancer Research Based on Physiotherapy and Oncology 49
Shraddha MOHITE, Suresh J. BHOSALE, Salim CHAVAN and Kadam SHRIKANT
2.1. Introduction 50
2.2. Role of AI in oncology and physiotherapy 50
2.3. AI model development pipeline in cancer research 52
2.4. Validation techniques 57
2.5. Key metrics for model evaluation 60
2.6. Challenges in validation for cancer physiotherapy models 63
2.7. Regulatory and ethical considerations 65
2.8. Future directions 67
2.9. Conclusion 67
2.10. References 68
Chapter 3. The Role of Artificial Intelligence in Personalized Physiotherapy and Cancer Treatment 73
S. ANANDH, Suresh J. BHOSALE and Sachin Purushottam UNTAWALE
3.1. Introduction 73
3.2. Overview of AI in healthcare 75
3.3. Personalized physiotherapy 78
3.4. Personalized cancer treatment 79
3.5. Challenges and ethical considerations 82
3.6. Prospects 83
3.7. Conclusion 84
3.8. References 85
Chapter 4. Machine Learning in Oncology and Physiotherapy: A New Era of Precision Medicine 89
Mandar MALAWADE, Shrushti P. JACHAK, Anand GUDUR and Sanjay L. BADJAT
4.1. Introduction 89
4.2. Machine learning in oncology 91
4.3. Machine learning in physiotherapy 94
4.4. Challenges and limitations 98
4.5. Future directions 99
4.6. Conclusion 100
4.7. References 101
Chapter 5. The Role of Physiotherapy in Enhancing Functional Recovery: Techniques, Benefits and Clinical Perspectives 105
Radhika CHINTAMANI, G. VARADHARAJULU and G. HIMASHREE
5.1. Introduction 106
5.2. Neural tissue mechanics 108
5.3. Material properties 113
5.4. Quasi-linear viscoelasticity 115
5.5. Load-deformation curve 118
5.6. Conclusion 122
5.7. References 123
Chapter 6. AI-Powered Rehabilitation: Transforming Physiotherapy for Cancer Survivors 127
Namrata KADAM, Suresh J. BHOSALE and Piyush Ashokrao DALKE
6.1. Introduction 128
6.2. The burden of cancer survivorship 129
6.3. AI in healthcare and rehabilitation 131
6.4. Personalized rehabilitation for cancer survivors 132
6.5. Remote monitoring and tele-rehabilitation 133
6.6. Enhancing patient engagement and motivation 134
6.7. Clinical outcomes and evidence-based practice 135
6.8. Challenges and ethical considerations 137
6.9. Future directions and recommendations 137
6.10. Conclusion 138
6.11. References 139
Chapter 7. Future Directions in Oncology: Emerging Technologies and Artificial Intelligence in Physiotherapy 143
Chandrakant PATIL, Dhiraj Kumar MANE, Anand GUDUR and Kalpana MALPE
7.1. Introduction 144
7.2. Emerging technologies in oncology physiotherapy 145
7.3. AI in oncology physiotherapy 150
7.4. Integration of technologies and AI in clinical practice 151
7.5. Challenges and ethical considerations 154
7.6. Future directions 155
7.7. Conclusion 156
7.8. References 157
Chapter 8. Deep Learning in Oncology and Physiotherapy: Enhancing Diagnosis and Recovery 161
Poonam PATIL, Neeraja ASWALE, Dhiraj Kumar MANE and Anand GUDUR
8.1. Introduction 161
8.2. DL fundamentals 162
8.3. DL applications in oncology 164
8.4. DL applications in physiotherapy 167
8.5. Challenges and limitations 170
8.6. Case studies 172
8.7. Future directions 173
8.8. Conclusion 173
8.9. References 174
Chapter 9. Automating Cancer Detection and Rehabilitation: The AI Revolution 179
Suraj KANASE, Rashmi GUDUR and Rasika MANAPU
9.1. Introduction 180
9.2. AI in cancer detection 182
9.3. Predictive analytics and risk assessment 185
9.4. Personalized treatment planning 187
9.5. AI in cancer rehabilitation 189
9.6. Challenges and ethical considerations 191
9.7. Case studies and clinical applications 192
9.8. Future directions 193
9.9. Conclusion 193
9.10. References 194
Chapter 10. Physiotherapy: A Holistic Approach to Rehabilitation and Functional Wellness 199
G. HIMASHREE, Radhika CHINTAMANI and G. VARADHARAJULU
10.1. Introduction 199
10.2. AI in biomaterials 201
10.3. History 201
10.4. Biomaterials: properties, types and applications 202
10.5. Metals 205
10.6. Ceramics and glasses 210
10.7. Polymers 213
10.8. Natural materials and composites 215
10.9. Conclusion 216
10.10. References 216
Chapter 11. AI and Wearable Technology in Physiotherapy for Oncology Patients 221
Trupti YADAV, Anand GUDUR and Vibha VYAS
11.1. Introduction 222
11.2. Background and motivation 224
11.3. Wearable technology in oncology physiotherapy 226
11.4. AI in oncology physiotherapy 227
11.5. Case studies and clinical trials 229
11.6. Benefits and clinical impact 231
11.7. Challenges and limitations 232
11.8. Future directions 234
11.9. Conclusion 235
11.10. References 236
Chapter 12. Smart Robotics in Physiotherapy and Oncology: Redefining Patient Outcomes 239
Pragati SALUNKHE, Suresh J. BHOSALE and Prashant S. JADHAV
12.1. Introduction 240
12.2. Background and technological foundations 241
12.3. Smart robotics in physiotherapy 243
12.4. Smart robotics in oncology 246
12.5. Integration with AI 248
12.6. Challenges and limitations 252
12.7. Future directions 253
12.8. Conclusion 253
12.9. References 254
Chapter 13. Recurrent Neural Networks for Predictive Modeling in Cancer Time Series Data 257
Mayiri BURUNGALE, Suresh J. BHOSALE, Rashmi GUDUR and Shamla MANTRI
13.1. Introduction 257
13.2. Background and related work 258
13.3. RNN architectures 260
13.4. Datasets and preprocessing 263
13.5. Applications in cancer prediction 267
13.6. Evaluation metrics 268
13.7. Challenges and limitations 269
13.8. Future directions 269
13.9. Conclusion 271
13.10. References 271
Chapter 14. The Role of Physiotherapy in Enhancing Functional Recovery in Musculoskeletal and Neurological Conditions 275
G. VARADHARAJULU, Radhika CHINTAMANI and G. HIMASHREE
14.1. Introduction 276
14.2. Hierarchical structure of cortical bone 277
14.3. Psychological support 285
14.4. Application of artificial intelligence (AI) in tissue regeneration 285
14.5. Conclusion 288
14.6. References 288
Chapter 15. Biomechanics in Physiotherapy 291
Sougata PANDA and Seveka BALI
15.1. Introduction 291
15.2. Methodology 294
15.3. Literature review 294
15.4. Results 304
15.5. Discussion. 305
15.6. Conclusion 306
15.7. References 306
Chapter 16. Role of Physiotherapy in Cancer Recovery: A Review and Recommendation 317
Sougata PANDA
16.1. Introduction 317
16.2. Literature review 319
16.3. Methods 322
16.4. Result 322
16.5. Discussion. 327
16.6. Recommendations 327
16.7. Conclusion 328
16.8. References 328
Chapter 17. The Role of Artificial Intelligence in Modern Healthcare: Transforming Diagnosis, Treatment and Rehabilitation 335
Mamta
17.1. Introduction to artificial intelligence (AI) in healthcare 335
17.2. Literature review 337
17.3. Methodology 340
17.4. How AI is disrupting healthcare today 342
17.5. Applications of AI across medical domains 343
17.6. Benefits of AI in healthcare 346
17.7. Challenges and ethical issues 348
17.8. The future of AI in healthcare 351
17.9. Conclusion 354
17.10. References 355
Chapter 18. Foundation of Artificial Intelligence in Healthcare 359
RUCHI, BAANI, Vikas WASSON and Kamini JOSHI
18.1. Introduction 360
18.2. Overview of AI 362
18.3. AI applications in medicine: literature review 365
18.4. AI-based healthcare: methodologies 370
18.5. Conclusion and future scope 378
18.6. References 379
List of Authors 385
Index 389
Summary of Volume 1 391
