Showing 1 - 7 of 7 Research Library Publications
Posted: | Erfan Khalaji, Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva

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.

Posted: | Victoria Yaneva, Brian E. Clauser, Amy Morales, Miguel Paniagua

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.

Posted: | Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva, Simon Harper

ACM SIGACCESS Accessibility and Computing

 

In this article, we first summarise STA (Scanpath Trend Analysis) with its application in autism detection, and then discuss future directions for this research.

Posted: | M. M. Hammoud, L. M.Foster, M. M.Cuddy, D. B. Swanson, P. M. Wallach

American Journal of Obstetrics and Gynecology, Volume 223, Issue 3, Pages 435.e1-435.e6

 

The purpose of this study was to examine medical student reporting of electronic health record use during the obstetrics and gynecology clerkship.

Posted: | V. Yaneva, L. A. Ha, S. Eraslan, Y. Yesilada, R. Mitkov

IEEE Transactions on Neural Systems and Rehabilitation Engineering

 

The purpose of this study is to test whether visual processing differences between adults with and without high-functioning autism captured through eye tracking can be used to detect autism.

Posted: | P. M. Wallach L. M. Foster, M. M. Cuddy, M. M. Hammoud, K. Z. Holtzman, D. B. Swanson

J Gen Intern Med 34, 705–711 (2019)

 

This study examines medical student accounts of EHR use during their internal medicine (IM) clerkships and sub-internships during a 5-year time period prior to the new clinical documentation guidelines.

Posted: | L. M. Foster, M. M. Cuddy, D. B. Swanson, K. Z. Holtzman, M. M. Hammoud, P. M. Wallach

Academic Medicine: November 2018 - Volume 93 - Issue 11S - p S14-S20

 

An important goal of medical education is to teach students to use an electronic health record (EHR) safely and effectively. The purpose of this study is to examine medical student accounts of EHR use during their core inpatient clinical clerkships using a national sample. Paper health records (PHRs) are similarly examined.