Anaïs Couret, Maryse Lapeyre-Mestre, Axel Renoux, Virginie Gardette
Healthcare use according to deprivation among French Alzheimer's Disease and Related Diseases subjects: a national cross-sectional descriptive study based on the FRA-DEM cohort
Frontiers in public health
artificial intelligence ai machine learning ml poised substantial impact health care space plethora webbased resources exist teach programming skills ml model development introductory curricula specifically tailored medical students without background data science programming programs exist often restricted specific specialty hypothesized 1month elective fourthyear medical students composed highquality existing webbased resources projectbased structure would empower students learn impact ai ml chosen specialty begin contributing innovation field interest study aims evaluate success elective improving selfreported confidence scores ai ml authors also share curriculum educators may interested adoption elective offered 2 tracks technical students already competent programmers nontechnical technical prerequisites focusing building conceptual understanding ai ml students established conceptual foundation knowledge using curated webbased resources relevant research papers tasked completing 3 projects chosen specialty data set analysis literature review ai project proposal projectbased nature elective designed selfguided flexible students interest area career goals students success measured selfreported confidence ai ml skills pre postsurveys qualitative feedback students experiences also collected webbased selfdirected elective offered passorfail basis month fourthyear students emory university school medicine beginning may 2021 june 2022 total 19 students successfully completed elective representing wide range chosen specialties diagnostic radiology n3 general surgery n1 internal medicine n5 neurology n2 obstetrics gynecology n1 ophthalmology n1 orthopedic surgery n1 otolaryngology n2 pathology n2 pediatrics n1 students selfreported confidence scores ai ml rose 66 1month elective qualitative surveys students overwhelmingly reported enthusiasm satisfaction course commented selfdirection flexibility projectbased design course essential course participants successful diving deep applications ai widelyranging specialties produced substantial project deliverables generally reported satisfaction elective experience authors hopeful brief 1month investment ai ml education medical school empower next generation physicians pave way ai ml innovation health care