RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
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.
Academic Medicine: Volume 97 - Issue 8 - Pages 1219-1225
Since 2012, the United States Medical Licensing Examination (USMLE) has maintained a policy of ≤ 6 attempts on any examination component. The purpose of this study was to empirically examine the appropriateness of existing USMLE retake policy.
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.
Academic Medicine: Volume 97 - Issue 4 - Pages 476-477
Response to to emphasize that although findings support a relationship between multiple USMLE attempts and increased likelihood of receiving disciplinary actions, the findings in isolation are not sufficient for proposing new policy on how many attempts should be allowed.
Academic Medicine: Volume 97 - Issue 2 - Pages 262-270
This study examined shifts in U.S. medical student interactions with EHRs during their clinical education, 2012–2016, and how these interactions varied by clerkship within and across medical schools.