AUTHOR=Duy Tran Long Cong , Metwalli Helal , Tien Le Dat , Amo-Afful Samuel , Todry Gerges Mario Salib , Hassan Ahmed Hajer Hatim , Kim Quyen Dinh Thi , Gamil Gad Abdelrahman , Tran Phillip , Huy Nguyen Tien 

TITLE=Learning new surgical techniques in low and middle income countries, approval processes, and the impact of artificial intelligence

JOURNAL=Frontiers in Surgery

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/surgery/articles/10.3389/fsurg.2025.1647899

DOI=10.3389/fsurg.2025.1647899

ISSN=2296-875X

ABSTRACT=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.