A comprehensive exploration of artificial intelligence in orthopaedics within lower-middle-income countries: a narrative review Authors Umm E Salma Shabbar Banatwala 3rd Year MBBS Student, Dow University of Health Sciences Muhammad Talal Ibrahim Department of Surgery, Section of Orthopaedics, Aga Khan University Hospital Reyan Hussain Shaikh 1st Year MBBS Student, Medical College, Aga Khan University, Karachi, Pakistan. Hania Shahzad Department of Orthopaedics, UC Davis Health, Sacramento, California, USA. Zahra Hoodbhoy Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan Shahryar Noordin Department of Surgery, Section of Orthopaedics, Aga Khan University Hospital DOI: https://doi.org/10.47391/JPMA.AKU-9S-14 Abstract Integrating Artificial Intelligence (AI) in orthopaedic within lower-middle-income countries (LMICs) promises landmark improvement in patient care. Delving into specific use cases—fracture detection, spine imaging, bone tumour classification, and joint surgery optimisation—the review illuminates the areas where AI can significantly enhance orthopaedic practices. AI could play a pivotal role in improving diagnoses, enabling early detection, and ultimately enhancing patient outcomes— crucial in regions with constrained healthcare services. Challenges to the integration of AI include financial constraints, shortage of skilled professionals, data limitations, and cultural and ethical considerations. Emphasising AI's collaborative role, it can act as a complementary tool working in tandem with physicians, aiming to address gaps in healthcare access and education. We need continued research and a conscientious approach, envisioning AI as a catalyst for equitable, efficient, and accessible orthopaedic healthcare for patients in LMICs. Keywords: Artificial Intelligence, Orthopaedics, Health Services, Patient Care, Bone Neoplasms, Physicians, precision medicine; predictive analysis Downloads Full Text Article Published 2024-05-03 How to Cite Umm E Salma Shabbar Banatwala, Muhammad Talal Ibrahim, Reyan Hussain Shaikh, Hania Shahzad, Zahra Hoodbhoy, & Shahryar Noordin. (2024). A comprehensive exploration of artificial intelligence in orthopaedics within lower-middle-income countries: a narrative review. Journal of the Pakistan Medical Association, 74(4), S–90. https://doi.org/10.47391/JPMA.AKU-9S-14 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX Issue Vol. 74 No. 4 (2024): 9th AKU Annual Surgical Conference - Surgery In The Digital Era Section NARRATIVE REVIEW License Copyright (c) 2024 Journal of the Pakistan Medical Association This work is licensed under a Creative Commons Attribution 4.0 International License.