RESEARCH LIBRARY

Advances in Health Sciences Education: Volume 25, p 1057–1086 (2020)

This critical review explores: (1) published applications of data science and ML in HPE literature and (2) the potential role of data science and ML in shifting theoretical and epistemological perspectives in HPE research and practice.

Academic Medicine: July 2019 - Volume 94 - Issue 7 - p 926-927

A response to concerns regarding potential bias in the implementation of machine learning (ML) to scoring of the United States Medical Licensing Examination Step 2 Clinical Skills (CS) patient notes (PN).

Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 314-316

The United States Medical Licensing Examination Step 2 Clinical Skills (CS) exam uses physician raters to evaluate patient notes written by examinees. In this Invited Commentary, the authors describe the ways in which the Step 2 CS exam could benefit from adopting a computer-assisted scoring approach that combines physician raters’ judgments with computer-generated scores based on natural language processing (NLP).

Journal of Medical Regulation (2018) 104 (2): 51–57

There have been a number of important stakeholder opinions critical of the Step 2 Clinical Skills Examination (CS) in the United States Medical Licensing Examination (USMLE) licensure sequence. The Resident Program Director (RPD) Awareness survey was convened to gauge perceptions of current and potential Step 2 CS use, attitudes towards the importance of residents' clinical skills, and awareness of a medical student petition against Step 2 CS. This was a cross-sectional survey which resulted in 205 responses from a representative sampling of RPDs across various specialties, regions and program sizes.