Artificial Intelligence and Machine Learning in Orthopedics: Current Applications, Limitations, and Future Directions in the Indian Context
Year: 2026
Type: article
Abstract: Background: Artificial intelligence (AI) and machine learning (ML) are transforming orthopedic care by augmenting diagnostic precision, preoperative planning, and outcome prediction.These tools analyze complex imaging and clinical data at scales that are unattainable by human cognition.Objective: To synthesize evidence on current applications of AI and ML in orthopedics, highlight clinical benefits, and evaluate implementation challenges within the Indian healthcare system.Methods: A narrative review of more than 70 peer-reviewed publications (2018-2025) retrieved from PubMed, Scopus, and Google Scholar was performed.Literature addressing AI in imaging, robotic surgery, and predictive analytics was prioritized for clinical relevance.Results: Artificial intelligence systems demonstrate 15-25% higher diagnostic accuracy for fracture detection and arthritis grading compared with conventional interpretation.Machine learning-driven models assist in implant templating, robotic navigation, and rehabilitation analytics.Barriers include limited datasets, regulatory ambiguity, and cost constraints.Conclusion: Artificial intelligence will enhance-not replace-the orthopedic surgeon.Responsible integration supported by clinician involvement, data quality, and ethical governance will enable equitable, high-precision orthopedic care in India.
Source: Journal of Orthopedic Advances
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W7225693403