MINI REVIEW article
Front. Surg.
Sec. Orthopedic Surgery
Volume 12 - 2025 | doi: 10.3389/fsurg.2025.1647899
This article is part of the Research TopicTransforming Surgical Care in the Global South: Enhancing Quality and AccessibilityView all articles
Learning New Surgical Techniques in Low and Middle Income Countries, Approval Processes, and the Impact of Artificial Intelligence
Provisionally accepted
Long Cong Duy Tran1Helal Metwalli2
Dat Tien Le1
Samuel Amo-Afful3Mario Salib Todry Gerges4Hajer Hatim Hassan Ahmed5Dinh Thi Kim Quyen6
Abdelrahman Gamil Gad7Phillip Tran8
Nguyen Tien Huy9*- 1Department of Hepatobiliary and Pancreatic Surgery, University Medical Center at Ho Chi Minh City Vietnam ., Ho Chi Minh City, Vietnam
- 2Benha University Faculty of Medicine, Banha, Egypt
- 3Queen Alexandra Hospital United Kingdom, Portsmouth PO6 3LY,, United Kingdom
- 4Mokattam Insurance Hospital, Egypt., Cairo,, Egypt
- 5Faculty of Medicine, Alzaiem Alazhari University, Sudan, Khartoum, Sudan
- 6Pediatric Surgery Department, University of Medicine and Pharmacy at Ho Chi Minh City, , Vietnam, Ho Chi Minh City 70000, Vietnam
- 7Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, USA, Baltimore, Maryland, United States
- 8Invasive Cardiology Nam Can Tho University, Vietnam, Can Tho,, Vietnam
- 9School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
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Training in surgery and approval of new techniques in low-and middle-income countries (LMICs), usually depends on informal apprenticeship systems, that is often lacking standardization, structured mentorship and produce inconsistent patient outcomes. These challenges are particularly severe in rural areas, where training opportunities and healthcare infrastructure are limited. Recently, artificial intelligence (AI) has emerged as a reliable solution, providing applicable, Quantitative methods for skill development, competency evaluation and regulatory supervision. AI-powered tools, such as virtual reality (VR) simulations and tele-mentoring platforms, provide independent skill assessments and expand access to high-quality surgical education. However, implementing AI in LMICs faces some challenges, including inadequate resources, financial constraints and ethical issues related to data security and Equitable algorithms. This review compares usual surgical training and approval processes in LMICs and evaluates the promising role of AI to fill existing gaps and compares both approaches in terms of applicability, cost-effectiveness and impact on patient outcomes.
Keywords: Surgery, Artificia l Intelligence, LMIC (low and middle income countries), healthcare, residency accreditation
Received: 16 Jun 2025; Accepted: 14 Jul 2025.
Copyright: © 2025 Duy Tran, Metwalli, Tien Le, Amo-Afful, Todry Gerges, Hassan Ahmed, Kim Quyen, Gamil Gad, Tran and Huy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Nguyen Tien Huy, School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
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