Artificial Intelligence in Medical and Psychological Education: A Scoping Review and Suggested Curriculum for Medical Students (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Artificial intelligence (AI) is revolutionizing healthcare, significantly enhancing diagnostic accuracy, clinical decision-making, and operational efficiency. However, the pace of AI integration into medical education has lagged behind, leaving students inadequately prepared for the emerging challenges AI brings to healthcare. Key issues such as AI’s ethical implications, transparency, and inherent biases remain critical concerns that need to be addressed. While there is growing support for AI’s role in medical practice, many medical curricula still lack structured AI training programs, limiting students’ ability to fully leverage AI’s potential. </sec> <sec> <title>OBJECTIVE</title> This paper reviews the current state of AI education programs in medical and psychology training and proposes a model AI curriculum that can be used as a case example to illustrate how AI can be integrated effectively into medical education. </sec> <sec> <title>METHODS</title> A scoping review was conducted following the PRISMA-ScR guidelines to analyze existing AI education programs. Searches were performed in PubMed, PsycINFO, and Web of Science (2008–2023) for relevant studies. The inclusion criteria focused on programs designed for medical and psychological professionals. Data were extracted, synthesized narratively, and visualized. Screening was performed using Rayyan, and disagreements were resolved by reviewers. </sec> <sec> <title>RESULTS</title> From 5,364 records, 20 relevant programs were identified. The majority of programs (50%) were from the United States, with others coming from Canada, Germany, France, China, and the Netherlands. Topics covered included foundational AI concepts, programming, ethical concerns, governance, and AI’s role in clinical decision-making. Most programs were extracurricular (60%), and evaluation results highlighted that while technical skills were often taught, many programs lacked in-depth practical applications or hands-on experience with AI tools. Ethical and governance topics were also a common focus. In light of these findings, we propose five principles for a successful curriculum with a strong psychiatric perspective in order to both improve skills on AI and increase the attractiveness of psychiatry among medical students. </sec> <sec> <title>CONCLUSIONS</title> The integration of AI into medical and psychology curricula is essential for producing well-rounded healthcare professionals. To prepare students for AI’s role in healthcare, educational programs should be mandatory and focus on foundational AI knowledge, ethical considerations, data privacy, and clinical decision-making. These programs should align with the WHO’s guiding principles, ensuring that topics such as Explainable AI, Natural Language Processing (NLP), and algorithmic biases are comprehensively covered. Furthermore, it is crucial to foster collaboration with universities in low- and middle-income countries (LMICs) to ensure equitable access to AI education, bridging global disparities in healthcare technology. Such efforts will contribute to the sustainable, inclusive growth of AI in healthcare, enabling all healthcare systems to benefit from advancements in AI technologies. </sec>

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