RESEARCH LIBRARY

Springer International Publishing; 2019

This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification.

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.