RESEARCH LIBRARY

Academic Medicine: Volume 97 - Issue 11S - Page S176

As Step 1 begins to transition to pass/fail, it is interesting to consider the impact of score goal on wellness. This study examines the relationship between goal score, gender, and students’ self-reported anxiety, stress, and overall distress immediately following their completion of Step 1.

Behavior & Information Technology

This study builds upon prior work in this area that focused on developing a machine-learning classifier trained on gaze data from web-related tasks to detect ASD in adults. Using the same data, we show that a new data pre-processing approach, combined with an exploration of the performance of different classification algorithms, leads to an increased classification accuracy compared to prior work.

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - p 2880–2886

This paper presents a corpus of 43,985 clinical patient notes (PNs) written by 35,156 examinees during the high-stakes USMLE® Step 2 Clinical Skills examination.

Academic Medicine: June 2022

This study examines the associations between Step 3 scores and subsequent receipt of disciplinary action taken by state medical boards for problematic behavior in practice. It analyzes Step 3 total, Step 3 computer-based case simulation (CCS), and Step 3multiple-choice question (MCQ) scores.

Journal of Graduate Medical Education: Volume 14, Issue 3, Pages 353-354

Letter to the editor.

Advances in Health Sciences Education: Volume 27, p 1401–1422

After collecting eye-tracking data from 26 students responding to clinical MCQs, analysis is performed by providing 119 eye-tracking features as input for a machine-learning model aiming to classify correct and incorrect responses. The predictive power of various combinations of features within the model is evaluated to understand how different feature interactions contribute to the predictions.