A Model to Introduce Medical Students to the Use of Artificial Intelligence and Genomics for Precision Medicine

ObjectiveDespite the significant medical impact of artificial intelligence (AI) in healthcare, emergence of AI-related topics in medical curricula has been slow. The authors sought to introduce pre-clinical students to the importance of AI methodologies and medical applications using modular short courses focused on active learning with precision medicine as a primary use case. Materials and MethodsA short elective course was designed to introduce first-year students to how various bioinformatic and AI-related processes work and how they help classify medical data, facilitate genomic analysis and predict clinical outcomes. The course covers gene sequencing and variants, neural networks, natural language processing, medical computer vision and the limitations and ethical concerns related to use of AI in precision medicine. Online content serves as major source material. After a faculty-led introduction, sessions focus on teams of students who present course content to one another and lead discussions with faculty guidance. A related short AI course focused on gene variants was given to the entire second-year class. ResultsThe elective course has been taken by 74 first- year students over 8 consecutive semesters (2017-2021). The course achieved average satisfaction scores of 4.4/5.0 (n = 13) when the active learning approach became dominant in 2018. Students were able to describe accurately how bioinformatics and AI make personalized medicine possible. Students also did well on the gene variants exercise given to the entire second year class (2018), but the full class short AI course was not continued in subsequent years. Students have created a school-approved interest group in medical AI. ConclusionsThis experience shows that AI-related materials can be sustainably introduced into pre- clinical medical education with precision medicine as the primary use case. This modular course design and content could be adapted easily for educational use in medical subspecialties and other health professions.