Abhishek Kumar is a senior IEEE member and professor at Chandigarh University in Mohali, India. His research expertise spans AI, renewable energy and image processing.Priya Batta is an associate professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her research specializes in AI, blockchain and the IoT.

• Preface xiAbhishek KUMAR and Priya BATTAChapter 1. AI-Assisted Comparison of Volar Plating with and Without Carpal Tunnel Release in Distal Radius Fractures 1Abhishek SHARMA and Paresh V. PATIL1.1. Introduction 21.2. Literature review 41.3. Materials and methods 61.3.1. Study setting and ethical approval 61.3.2. Study population and sample size 61.3.3. Inclusion criteria 71.3.4. Exclusion criteria 71.3.5. Study Groups 81.3.6. Preoperative assessment 81.3.7. Trauma-surgery interval 81.3.8. Observation and result 91.4. Discussion 181.5. Conclusion 201.6. References 20Chapter 2. Trigger Digits: Steroid Injection Versus Percutaneous Release Using AI-Based Outcome Analysis 23Anshuraj JAGDALE and Jineshwar S. KAPALE2.1. Introduction 232.2. Literature review 262.3. Conservative management: LSI 272.4. PR: technique and outcomes 272.5. Comparative efficacy: steroid injection versus PR. 282.6. Complications and safety considerations 292.7. Meta-analyses and systematic reviews 292.8. Clinical implications and future directions 292.9. Materials and methods 302.9.1. Materials and method of selection 302.9.2. Conduction of study 302.9.3. Sample size 312.9.4. Statistical analysis 322.10. Observation and results 322.10.1. Age distribution 322.10.2. Sex distribution 332.10.3. Side distribution 342.10.4. Pre-operative analysis of Green's grading 342.10.5. Finger involvement 352.10.6. Efficacy of treatment modalities 362.10.7. Recurrence rate post-treatment 372.10.8. Longevity of symptom relief within the follow-up period 382.10.9. Tendon release assessment in the PR group 392.11. Complications 402.11.1. Tendon/neurovascular bundle injury 402.11.2. Infection rate 412.11.3. Post-treatment functional outcome assessment 412.12. Discussion 422.13. Conclusion 432.14. References 44Chapter 3. Rigid Versus Hybrid Fixation in Both-Bone Forearm Fractures: An AI-Supported Comparative Study 47Manthena Ramakrishna Vittal VERMA and Paresh V. PATIL3.1. Introduction 473.2. Literature review 493.2.1. Evolution of forearm fracture management 493.2.2. Rigid fixation using plate osteosynthesis 503.2.3. IMN of forearm bones 503.2.4. Hybrid fixation: concept and rationale 513.2.5. Comparative studies: rigid versus hybrid fixation 513.2.6. Functional outcomes and complications 513.2.7. Role of advanced and AI-assisted analysis 52Contents vii3.3. Materials and methods 523.3.1. Duration of study 523.3.2. Ethical approval 533.3.3. Study population 533.3.4. Inclusion criteria 533.3.5. Sample size 543.3.6. Observation and results 553.4. Discussion 663.5. Conclusion 673.6. References 68Chapter 4. Fracture Healing After Cephalomedullary Nailing with Zoledronic Acid: An AI-Driven Comparison 71Mrunal PATEL and Pradeep N. KULKARNI4.1. Introduction 714.2. Literature review 744.2.1. CMN and fracture healing 744.2.2. BPs and fracture healing 744.2.3. Mechanisms of ZA in bone healing 754.2.4. Clinical implications for CMN with ZA 764.2.5. AI-driven comparative approaches in orthopedic outcomes 764.3. Materials and methods 774.3.1. Sample size 774.3.2. Enrolment criteria 784.3.3. Study tool 784.4. Observation and results 794.4.1. AO Type 2 (comminuted, non-articular) 864.5. Discussion 904.6. Conclusion 914.7. References 91Chapter 5. Alpha-Blockers in Cervical Radiculopathy: An AI-Guided Efficacy Study 95Nidhi Vipul SHAH and Pradeep N. KULKARNI5.1. Introduction 955.2. Literature review 975.2.1. Cervical radiculopathy: epidemiology and etiology 975.2.2. Pathophysiology of cervical radiculopathy 985.2.3. Clinical presentation and diagnostic approaches 985.2.4. Conventional treatment modalities – NSAIDs 995.2.5. Cervical traction 995.2.6. Interventional pain management techniques 995.2.7. Epidural steroid injections and selective nerve root blocks 995.2.8. Physiological pain portal block (Alpha Portal Block) 1005.2.9. Alpha Portal Block in cervical radiculopathy 1005.2.10. Role of AI in outcome analysis 1005.3. Materials and methods 1015.3.1. Sample size calculation (explained) formula used 1015.3.2. Exclusion criteria 1015.4. Observation and results 1025.5. Discussion 1075.6. Conclusion 1085.7. References 109Chapter 6. Suprapatellar Versus Infrapatellar Tibial Nailing: AI-Assisted Outcome Comparison 113Nikhil DUDHANI and Nitin S. PATIL6.1. Introduction 1146.2. Literature review 1166.2.1. Epidemiology and management of tibial shaft fractures 1166.2.2. IP tibial nailing 1166.2.3. SP tibial nailing 1176.2.4. Comparative studies: SP versus IP approach 1176.2.5. Role of AI in orthopedic outcome analysis 1186.3. Materials and methods 1186.3.1. Study design 1186.3.2. Study setting 1196.3.3. Study duration 1196.3.4. Inclusion criteria 1196.3.5. Exclusion criteria 1196.4. Observation and results 1206.5. Discussion 1276.6. Conclusion 1286.7. References 129Chapter 7. AI-Based Functional Outcome Comparison of Nails in Unstable Intertrochanteric Femur Fracture. 133Chintalapuri Pranay Bhargav REDDY and Vikash A. SATRE7.1. Introduction 1337.2. Literature review 1367.3. Materials and methods 1387.3.1. Study configuration and design 1387.3.2. Quantity of the sample 138Contents ix7.3.3. Sampling method 1397.3.4. Inclusion criteria 1397.3.5. Exclusion criteria 1407.3.6. Ethical considerations 1407.3.7. Surgical procedure 1407.4. Observation and results 1407.4.1. Age distribution 1407.5. Discussion 1477.6. Conclusion 1487.7. References 149Chapter 8. Dynamic Condylar Screw Versus Long PFN in Subtrochanteric Fractures: An AI-Enhanced Study 153Rutul D. PATEL and Nitin S. PATIL8.1. Introduction 1548.2. Literature review 1568.2.1. Subtrochanteric femur fractures 1568.2.2. Evolution of surgical management 1568.2.3. DCS 1578.2.4. LPFN 1578.2.5. Comparative studies: DCS versus long PFN 1578.2.6. The role of AI in fracture outcome analysis 1588.3. Materials and methods 1588.3.1. Study design 1588.3.2. Ethical approval 1588.3.3. Study duration 1598.3.4. Sample size 1598.4. Observation and results 1608.5. Discussion 1708.6. Conclusion 1718.7. References 172Chapter 9. Mid-Shaft Humerus Fractures: AI-Supported Comparison of Fixation Methods 175Syed Nadeem AHAMED and Jineshwar S. KAPALE9.1. Introduction 1759.2. Literature review 1789.2.1. Operative fixation: overview and evolution 1789.2.2. Comparative evidence: plating versus nailing 1799.2.3. Minimally invasive plating and bridge techniques 1809.2.4. Functional outcomes and patient-reported measures 1809.2.5. Complications and risk profiles 1809.2.6. Current gaps and future directions 1809.3. Materials and methods 1819.3.1. Study design 1819.3.2. Study site 1819.3.3. Study duration 1819.3.4. Sample size calculation 1829.3.5. Sample size of approximately 35 for each group 1829.3.6. Exclusion criteria 1839.3.7. Surgical procedures 1839.4. Observation and results 1839.5. Discussion 1919.6. Conclusion 1929.7. References 192Chapter 10. ACL Reconstruction Using Peroneus Longus Versus Hamstring Graft: An AI-Based Outcome Study 195Viradraj Shrinivas DESHMUKH and Nishant GAONKAR10.1. Introduction 19510.2. Literature review 19810.2.1. HT graft 19910.2.2. Flap of PLT grafts 19910.2.3. Comparative studies between PL and hamstring grafts 19910.2.4. Application of AI in outcome evaluation 20010.3. Materials and methods 20010.3.1. Study design 20010.3.2. Sample size calculation. 20010.3.3. Sample selection and randomization 20210.3.4. Methods of data collection. 20310.4. Observation and results 20310.5. Discussion 21010.6. Conclusion 21110.7. References 211List of Authors 215Index 219

Abhishek Kumar is a senior IEEE member and professor at Chandigarh University in Mohali, India. His research expertise spans AI, renewable energy and image processing.Priya Batta is an associate professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her research specializes in AI, blockchain and the IoT.

• Preface xiAbhishek KUMAR and Priya BATTAChapter 1. AI-Assisted Comparison of Volar Plating with and Without Carpal Tunnel Release in Distal Radius Fractures 1Abhishek SHARMA and Paresh V. PATIL1.1. Introduction 21.2. Literature review 41.3. Materials and methods 61.3.1. Study setting and ethical approval 61.3.2. Study population and sample size 61.3.3. Inclusion criteria 71.3.4. Exclusion criteria 71.3.5. Study Groups 81.3.6. Preoperative assessment 81.3.7. Trauma-surgery interval 81.3.8. Observation and result 91.4. Discussion 181.5. Conclusion 201.6. References 20Chapter 2. Trigger Digits: Steroid Injection Versus Percutaneous Release Using AI-Based Outcome Analysis 23Anshuraj JAGDALE and Jineshwar S. KAPALE2.1. Introduction 232.2. Literature review 262.3. Conservative management: LSI 272.4. PR: technique and outcomes 272.5. Comparative efficacy: steroid injection versus PR. 282.6. Complications and safety considerations 292.7. Meta-analyses and systematic reviews 292.8. Clinical implications and future directions 292.9. Materials and methods 302.9.1. Materials and method of selection 302.9.2. Conduction of study 302.9.3. Sample size 312.9.4. Statistical analysis 322.10. Observation and results 322.10.1. Age distribution 322.10.2. Sex distribution 332.10.3. Side distribution 342.10.4. Pre-operative analysis of Green's grading 342.10.5. Finger involvement 352.10.6. Efficacy of treatment modalities 362.10.7. Recurrence rate post-treatment 372.10.8. Longevity of symptom relief within the follow-up period 382.10.9. Tendon release assessment in the PR group 392.11. Complications 402.11.1. Tendon/neurovascular bundle injury 402.11.2. Infection rate 412.11.3. Post-treatment functional outcome assessment 412.12. Discussion 422.13. Conclusion 432.14. References 44Chapter 3. Rigid Versus Hybrid Fixation in Both-Bone Forearm Fractures: An AI-Supported Comparative Study 47Manthena Ramakrishna Vittal VERMA and Paresh V. PATIL3.1. Introduction 473.2. Literature review 493.2.1. Evolution of forearm fracture management 493.2.2. Rigid fixation using plate osteosynthesis 503.2.3. IMN of forearm bones 503.2.4. Hybrid fixation: concept and rationale 513.2.5. Comparative studies: rigid versus hybrid fixation 513.2.6. Functional outcomes and complications 513.2.7. Role of advanced and AI-assisted analysis 52Contents vii3.3. Materials and methods 523.3.1. Duration of study 523.3.2. Ethical approval 533.3.3. Study population 533.3.4. Inclusion criteria 533.3.5. Sample size 543.3.6. Observation and results 553.4. Discussion 663.5. Conclusion 673.6. References 68Chapter 4. Fracture Healing After Cephalomedullary Nailing with Zoledronic Acid: An AI-Driven Comparison 71Mrunal PATEL and Pradeep N. KULKARNI4.1. Introduction 714.2. Literature review 744.2.1. CMN and fracture healing 744.2.2. BPs and fracture healing 744.2.3. Mechanisms of ZA in bone healing 754.2.4. Clinical implications for CMN with ZA 764.2.5. AI-driven comparative approaches in orthopedic outcomes 764.3. Materials and methods 774.3.1. Sample size 774.3.2. Enrolment criteria 784.3.3. Study tool 784.4. Observation and results 794.4.1. AO Type 2 (comminuted, non-articular) 864.5. Discussion 904.6. Conclusion 914.7. References 91Chapter 5. Alpha-Blockers in Cervical Radiculopathy: An AI-Guided Efficacy Study 95Nidhi Vipul SHAH and Pradeep N. KULKARNI5.1. Introduction 955.2. Literature review 975.2.1. Cervical radiculopathy: epidemiology and etiology 975.2.2. Pathophysiology of cervical radiculopathy 985.2.3. Clinical presentation and diagnostic approaches 985.2.4. Conventional treatment modalities – NSAIDs 995.2.5. Cervical traction 995.2.6. Interventional pain management techniques 995.2.7. Epidural steroid injections and selective nerve root blocks 995.2.8. Physiological pain portal block (Alpha Portal Block) 1005.2.9. Alpha Portal Block in cervical radiculopathy 1005.2.10. Role of AI in outcome analysis 1005.3. Materials and methods 1015.3.1. Sample size calculation (explained) formula used 1015.3.2. Exclusion criteria 1015.4. Observation and results 1025.5. Discussion 1075.6. Conclusion 1085.7. References 109Chapter 6. Suprapatellar Versus Infrapatellar Tibial Nailing: AI-Assisted Outcome Comparison 113Nikhil DUDHANI and Nitin S. PATIL6.1. Introduction 1146.2. Literature review 1166.2.1. Epidemiology and management of tibial shaft fractures 1166.2.2. IP tibial nailing 1166.2.3. SP tibial nailing 1176.2.4. Comparative studies: SP versus IP approach 1176.2.5. Role of AI in orthopedic outcome analysis 1186.3. Materials and methods 1186.3.1. Study design 1186.3.2. Study setting 1196.3.3. Study duration 1196.3.4. Inclusion criteria 1196.3.5. Exclusion criteria 1196.4. Observation and results 1206.5. Discussion 1276.6. Conclusion 1286.7. References 129Chapter 7. AI-Based Functional Outcome Comparison of Nails in Unstable Intertrochanteric Femur Fracture. 133Chintalapuri Pranay Bhargav REDDY and Vikash A. SATRE7.1. Introduction 1337.2. Literature review 1367.3. Materials and methods 1387.3.1. Study configuration and design 1387.3.2. Quantity of the sample 138Contents ix7.3.3. Sampling method 1397.3.4. Inclusion criteria 1397.3.5. Exclusion criteria 1407.3.6. Ethical considerations 1407.3.7. Surgical procedure 1407.4. Observation and results 1407.4.1. Age distribution 1407.5. Discussion 1477.6. Conclusion 1487.7. References 149Chapter 8. Dynamic Condylar Screw Versus Long PFN in Subtrochanteric Fractures: An AI-Enhanced Study 153Rutul D. PATEL and Nitin S. PATIL8.1. Introduction 1548.2. Literature review 1568.2.1. Subtrochanteric femur fractures 1568.2.2. Evolution of surgical management 1568.2.3. DCS 1578.2.4. LPFN 1578.2.5. Comparative studies: DCS versus long PFN 1578.2.6. The role of AI in fracture outcome analysis 1588.3. Materials and methods 1588.3.1. Study design 1588.3.2. Ethical approval 1588.3.3. Study duration 1598.3.4. Sample size 1598.4. Observation and results 1608.5. Discussion 1708.6. Conclusion 1718.7. References 172Chapter 9. Mid-Shaft Humerus Fractures: AI-Supported Comparison of Fixation Methods 175Syed Nadeem AHAMED and Jineshwar S. KAPALE9.1. Introduction 1759.2. Literature review 1789.2.1. Operative fixation: overview and evolution 1789.2.2. Comparative evidence: plating versus nailing 1799.2.3. Minimally invasive plating and bridge techniques 1809.2.4. Functional outcomes and patient-reported measures 1809.2.5. Complications and risk profiles 1809.2.6. Current gaps and future directions 1809.3. Materials and methods 1819.3.1. Study design 1819.3.2. Study site 1819.3.3. Study duration 1819.3.4. Sample size calculation 1829.3.5. Sample size of approximately 35 for each group 1829.3.6. Exclusion criteria 1839.3.7. Surgical procedures 1839.4. Observation and results 1839.5. Discussion 1919.6. Conclusion 1929.7. References 192Chapter 10. ACL Reconstruction Using Peroneus Longus Versus Hamstring Graft: An AI-Based Outcome Study 195Viradraj Shrinivas DESHMUKH and Nishant GAONKAR10.1. Introduction 19510.2. Literature review 19810.2.1. HT graft 19910.2.2. Flap of PLT grafts 19910.2.3. Comparative studies between PL and hamstring grafts 19910.2.4. Application of AI in outcome evaluation 20010.3. Materials and methods 20010.3.1. Study design 20010.3.2. Sample size calculation. 20010.3.3. Sample selection and randomization 20210.3.4. Methods of data collection. 20310.4. Observation and results 20310.5. Discussion 21010.6. Conclusion 21110.7. References 211List of Authors 215Index 219

Abhishek Kumar is a senior IEEE member and professor at Chandigarh University in Mohali, India. His research expertise spans AI, renewable energy and image processing.Priya Batta is an associate professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her research specializes in AI, blockchain and the IoT.

• Preface xiAbhishek KUMAR and Priya BATTAChapter 1. AI-Assisted Comparison of Volar Plating with and Without Carpal Tunnel Release in Distal Radius Fractures 1Abhishek SHARMA and Paresh V. PATIL1.1. Introduction 21.2. Literature review 41.3. Materials and methods 61.3.1. Study setting and ethical approval 61.3.2. Study population and sample size 61.3.3. Inclusion criteria 71.3.4. Exclusion criteria 71.3.5. Study Groups 81.3.6. Preoperative assessment 81.3.7. Trauma-surgery interval 81.3.8. Observation and result 91.4. Discussion 181.5. Conclusion 201.6. References 20Chapter 2. Trigger Digits: Steroid Injection Versus Percutaneous Release Using AI-Based Outcome Analysis 23Anshuraj JAGDALE and Jineshwar S. KAPALE2.1. Introduction 232.2. Literature review 262.3. Conservative management: LSI 272.4. PR: technique and outcomes 272.5. Comparative efficacy: steroid injection versus PR. 282.6. Complications and safety considerations 292.7. Meta-analyses and systematic reviews 292.8. Clinical implications and future directions 292.9. Materials and methods 302.9.1. Materials and method of selection 302.9.2. Conduction of study 302.9.3. Sample size 312.9.4. Statistical analysis 322.10. Observation and results 322.10.1. Age distribution 322.10.2. Sex distribution 332.10.3. Side distribution 342.10.4. Pre-operative analysis of Green's grading 342.10.5. Finger involvement 352.10.6. Efficacy of treatment modalities 362.10.7. Recurrence rate post-treatment 372.10.8. Longevity of symptom relief within the follow-up period 382.10.9. Tendon release assessment in the PR group 392.11. Complications 402.11.1. Tendon/neurovascular bundle injury 402.11.2. Infection rate 412.11.3. Post-treatment functional outcome assessment 412.12. Discussion 422.13. Conclusion 432.14. References 44Chapter 3. Rigid Versus Hybrid Fixation in Both-Bone Forearm Fractures: An AI-Supported Comparative Study 47Manthena Ramakrishna Vittal VERMA and Paresh V. PATIL3.1. Introduction 473.2. Literature review 493.2.1. Evolution of forearm fracture management 493.2.2. Rigid fixation using plate osteosynthesis 503.2.3. IMN of forearm bones 503.2.4. Hybrid fixation: concept and rationale 513.2.5. Comparative studies: rigid versus hybrid fixation 513.2.6. Functional outcomes and complications 513.2.7. Role of advanced and AI-assisted analysis 52Contents vii3.3. Materials and methods 523.3.1. Duration of study 523.3.2. Ethical approval 533.3.3. Study population 533.3.4. Inclusion criteria 533.3.5. Sample size 543.3.6. Observation and results 553.4. Discussion 663.5. Conclusion 673.6. References 68Chapter 4. Fracture Healing After Cephalomedullary Nailing with Zoledronic Acid: An AI-Driven Comparison 71Mrunal PATEL and Pradeep N. KULKARNI4.1. Introduction 714.2. Literature review 744.2.1. CMN and fracture healing 744.2.2. BPs and fracture healing 744.2.3. Mechanisms of ZA in bone healing 754.2.4. Clinical implications for CMN with ZA 764.2.5. AI-driven comparative approaches in orthopedic outcomes 764.3. Materials and methods 774.3.1. Sample size 774.3.2. Enrolment criteria 784.3.3. Study tool 784.4. Observation and results 794.4.1. AO Type 2 (comminuted, non-articular) 864.5. Discussion 904.6. Conclusion 914.7. References 91Chapter 5. Alpha-Blockers in Cervical Radiculopathy: An AI-Guided Efficacy Study 95Nidhi Vipul SHAH and Pradeep N. KULKARNI5.1. Introduction 955.2. Literature review 975.2.1. Cervical radiculopathy: epidemiology and etiology 975.2.2. Pathophysiology of cervical radiculopathy 985.2.3. Clinical presentation and diagnostic approaches 985.2.4. Conventional treatment modalities – NSAIDs 995.2.5. Cervical traction 995.2.6. Interventional pain management techniques 995.2.7. Epidural steroid injections and selective nerve root blocks 995.2.8. Physiological pain portal block (Alpha Portal Block) 1005.2.9. Alpha Portal Block in cervical radiculopathy 1005.2.10. Role of AI in outcome analysis 1005.3. Materials and methods 1015.3.1. Sample size calculation (explained) formula used 1015.3.2. Exclusion criteria 1015.4. Observation and results 1025.5. Discussion 1075.6. Conclusion 1085.7. References 109Chapter 6. Suprapatellar Versus Infrapatellar Tibial Nailing: AI-Assisted Outcome Comparison 113Nikhil DUDHANI and Nitin S. PATIL6.1. Introduction 1146.2. Literature review 1166.2.1. Epidemiology and management of tibial shaft fractures 1166.2.2. IP tibial nailing 1166.2.3. SP tibial nailing 1176.2.4. Comparative studies: SP versus IP approach 1176.2.5. Role of AI in orthopedic outcome analysis 1186.3. Materials and methods 1186.3.1. Study design 1186.3.2. Study setting 1196.3.3. Study duration 1196.3.4. Inclusion criteria 1196.3.5. Exclusion criteria 1196.4. Observation and results 1206.5. Discussion 1276.6. Conclusion 1286.7. References 129Chapter 7. AI-Based Functional Outcome Comparison of Nails in Unstable Intertrochanteric Femur Fracture. 133Chintalapuri Pranay Bhargav REDDY and Vikash A. SATRE7.1. Introduction 1337.2. Literature review 1367.3. Materials and methods 1387.3.1. Study configuration and design 1387.3.2. Quantity of the sample 138Contents ix7.3.3. Sampling method 1397.3.4. Inclusion criteria 1397.3.5. Exclusion criteria 1407.3.6. Ethical considerations 1407.3.7. Surgical procedure 1407.4. Observation and results 1407.4.1. Age distribution 1407.5. Discussion 1477.6. Conclusion 1487.7. References 149Chapter 8. Dynamic Condylar Screw Versus Long PFN in Subtrochanteric Fractures: An AI-Enhanced Study 153Rutul D. PATEL and Nitin S. PATIL8.1. Introduction 1548.2. Literature review 1568.2.1. Subtrochanteric femur fractures 1568.2.2. Evolution of surgical management 1568.2.3. DCS 1578.2.4. LPFN 1578.2.5. Comparative studies: DCS versus long PFN 1578.2.6. The role of AI in fracture outcome analysis 1588.3. Materials and methods 1588.3.1. Study design 1588.3.2. Ethical approval 1588.3.3. Study duration 1598.3.4. Sample size 1598.4. Observation and results 1608.5. Discussion 1708.6. Conclusion 1718.7. References 172Chapter 9. Mid-Shaft Humerus Fractures: AI-Supported Comparison of Fixation Methods 175Syed Nadeem AHAMED and Jineshwar S. KAPALE9.1. Introduction 1759.2. Literature review 1789.2.1. Operative fixation: overview and evolution 1789.2.2. Comparative evidence: plating versus nailing 1799.2.3. Minimally invasive plating and bridge techniques 1809.2.4. Functional outcomes and patient-reported measures 1809.2.5. Complications and risk profiles 1809.2.6. Current gaps and future directions 1809.3. Materials and methods 1819.3.1. Study design 1819.3.2. Study site 1819.3.3. Study duration 1819.3.4. Sample size calculation 1829.3.5. Sample size of approximately 35 for each group 1829.3.6. Exclusion criteria 1839.3.7. Surgical procedures 1839.4. Observation and results 1839.5. Discussion 1919.6. Conclusion 1929.7. References 192Chapter 10. ACL Reconstruction Using Peroneus Longus Versus Hamstring Graft: An AI-Based Outcome Study 195Viradraj Shrinivas DESHMUKH and Nishant GAONKAR10.1. Introduction 19510.2. Literature review 19810.2.1. HT graft 19910.2.2. Flap of PLT grafts 19910.2.3. Comparative studies between PL and hamstring grafts 19910.2.4. Application of AI in outcome evaluation 20010.3. Materials and methods 20010.3.1. Study design 20010.3.2. Sample size calculation. 20010.3.3. Sample selection and randomization 20210.3.4. Methods of data collection. 20310.4. Observation and results 20310.5. Discussion 21010.6. Conclusion 21110.7. References 211List of Authors 215Index 219