Jessie King, Barnaby Kelly, Nayla Rhein, Rhonda Rosengren
Post-COVID-19 approach to teaching an undergraduate laboratory class focused on experimental design and data interpretation
Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology
potential machine learning ml enhance efficiency medical specialty boards explored applied unsupervised ml identify archetypes among american board family medicine abfm diplomates regarding practice characteristics motivations participating continuing certification examined associations motivation patterns key recertification outcomes diplomates responding 2017 2021 abfm family medicine continuing certification examination surveys selected motivations choosing continue certification used chisquared tests examine difference proportions diplomates failing first recertification examination attempt endorsed different motivations maintaining certification unsupervised ml techniques applied generate clusters physicians similar practice characteristics motivations recertifying controlling physician demographic variables used logistic regression examine effect motivation clusters recertification examination success validated ml clusters comparison previously created classification schema developed experts ml clusters largely recapitulated intrinsicextrinsic framework devised experts previously however identified clusters achieved equal partitioning diplomates homogenous groups ml human clusters physicians mainly extrinsic mixed motivations lower rates examination failure intrinsically motivated study demonstrates feasibility using ml supplement enhance human interpretation board certification data discuss implications demonstration study interaction specialty boards physician diplomates