As healthcare landscapes evolve, Artificial intelligence (AI) has emerged as a transformative force in physiotherapy research in India. The integration of machine learning algorithms, computer vision, and natural language processing has significantly advanced the analysis of patient data, enabling the prediction of treatment outcomes and personalization of physiotherapy interventions. This overview delves into specific examples of successful AI integration in ongoing clinical trials within the Indian context, showcasing notable improvements in trial efficiency and positive impacts on patient outcomes. Challenges in implementing AI, including data security, ethical considerations, and the need for specialized training, are discussed. Proposed solutions encompass robust data encryption, ethical guidelines, interpretability of AI models, and targeted educational programs for healthcare professionals. Looking forward, the future outlook emphasizes personalized treatment plans, expanded tele physiotherapy using wearable technology, and the integration of augmented and virtual reality. Ethical and regulatory frameworks, continued advancements in robotic assistance, and interdisciplinary collaboration are highlighted as key factors shaping the trajectory of AI in physiotherapy clinical trials in India. The primary objectives of this manuscript are to explore the current state of AI in physiotherapy clinical trials in India, assess its utilization, and discuss the potential future developments in the field.

Annu Chhikara, Mansi Jain, Sakshi Vats, Faizan Z. Kashoo, Aksh Chahal, Sonali Guliya, Krishna Reddy Vajrala, Mohammad Sidiq, Richa Hirendra Rai. JLM 2023;13:90-6. https://doi.org/10.15280/jlm.2023.13.2.90

Background: Effectiveness and safety of Resistance Training in treating various Cerebrovascular Disease diagnoses have drawn attention in recent years. Patients suffering with coronary artery disease should be offered individually tailored Resistance Training in their exercise regimen. Resistance Training was developed to help individuals with their functional status, mobility, physical performance, and muscle strength. Objective: The objective of this review was to collect, summarize and present information on the state of science focusing on usefulness, viability, safety and efficacy of Resistance Training in treating coronary artery disease and enhancing the aerobic capacity and improving overall health-related quality of life. Methods: The review is prepared in accordance with Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. Searches were conducted in Cochrane Library, PubMed/MEDLINE, PEDro and Scopus database. PEDro scale was used for methodological quality assessment of included studies. Two independent reviewers determined the inclusion criteria of studies by classifying interventions based on core components, outcome measures, diagnostic population and rated the quality of evidence and strength of recommendations using GRADE criteria. Results: Total 13 studies with 1025 patients were included for the detailed analysis. Findings emphasize the importance of assessing effectiveness and safety of Resistance Training in individuals with coronary artery disease. Patient specific designed exercise programs as Resistance Training targets at enhancing patients’ exercise tolerance, improves hemodynamic response and muscular strength with reduction in body fat composition. Conclusion: Resistance Training is an effective exercise that should be incorporated to counteract the loss of muscle strength, muscle mass, and physiological vulnerability, as well as to combat the associated debilitating effects on physical functioning, mobility and overall independence and Quality of Life during rehabilitation of patients with coronary artery disease.