This paper is in the following e-collection/theme issue:

Clinical Informatics (1022) Artificial Intelligence (1371) Electronic Health Records (1053) Machine Learning (1465)

Published on in Vol 22, No 4 (2020): April

Leveraging Eye Tracking to Prioritize Relevant Medical Record Data: Comparative Machine Learning Study

Leveraging Eye Tracking to Prioritize Relevant Medical Record Data: Comparative Machine Learning Study

Leveraging Eye Tracking to Prioritize Relevant Medical Record Data: Comparative Machine Learning Study

Authors of this article:

Andrew J King1, 2 Author Orcid Image ;   Gregory F Cooper1, 3 Author Orcid Image ;   Gilles Clermont2 Author Orcid Image ;   Harry Hochheiser1, 3 Author Orcid Image ;   Milos Hauskrecht4 Author Orcid Image ;   Dean F Sittig5 Author Orcid Image ;   Shyam Visweswaran1, 3 Author Orcid Image
Article Authors Cited by (16) Tweetations (18) Metrics

Journals

  1. Wronski P, Wensing M, Ghosh S, Gärttner L, Müller W, Koetsenruijter J. Use of a quantitative data report in a hypothetical decision scenario for health policymaking: a computer-assisted laboratory study. BMC Medical Informatics and Decision Making 2021;21(1) View
  2. Seifer D, Mcgrath K, Scholl G, Mohan V, Gold J. Sex Differences in Electronic Health Record Navigation Strategies: Secondary Data Analysis. JMIR Human Factors 2021;8(2):e25957 View
  3. Shin G, Lee Y, Park T, Cho I, Yun M, Bahn S, Lee J. Investigation of usability problems of electronic medical record systems in the emergency department. Work 2022;72(1):221 View
  4. Kołodziej P, Tuszyńska-Bogucka W, Dzieńkowski M, Bogucki J, Kocki J, Milosz M, Kocki M, Reszka P, Kocki W, Bogucka-Kocka A. Eye Tracking—An Innovative Tool in Medical Parasitology. Journal of Clinical Medicine 2021;10(13):2989 View
  5. King A, Calzoni L, Tajgardoon M, Cooper G, Clermont G, Hochheiser H, Visweswaran S. A simple electronic medical record system designed for research. JAMIA Open 2021;4(3) View
  6. Visweswaran S, King A, Tajgardoon M, Calzoni L, Clermont G, Hochheiser H, Cooper G. Evaluation of eye tracking for a decision support application. JAMIA Open 2021;4(3) View
  7. Sugimoto M, Tomita A, Oyamada M, Sato M. Eye-Tracking-Based Analysis of Situational Awareness of Nurses. Healthcare 2022;10(11):2131 View
  8. Wei Q, Cao H, Shi Y, Xu X, Li T. Machine learning based on eye-tracking data to identify Autism Spectrum Disorder: A systematic review and meta-analysis. Journal of Biomedical Informatics 2023;137:104254 View
  9. King A, Kahn J, Brant E, Cooper G, Mowery D. Initial Development of an Automated Platform for Assessing Trainee Performance on Case Presentations. ATS Scholar 2022;3(4):548 View
  10. Vijayakumar S, P. S. N. Use of Natural Language Processing in Software Requirements Prioritization – A Systematic Literature Review. International Journal of Applied Engineering and Management Letters 2021:152 View
  11. Clermont G. The Learning Electronic Health Record. Critical Care Clinics 2023;39(4):689 View
  12. King A, Kahn J. The Role of Data Science in Closing the Implementation Gap. Critical Care Clinics 2023;39(4):701 View
  13. King A, Angus D, Cooper G, Mowery D, Seaman J, Potter K, Bukowski L, Al-Khafaji A, Gunn S, Kahn J. A voice-based digital assistant for intelligent prompting of evidence-based practices during ICU rounds. Journal of Biomedical Informatics 2023;146:104483 View
  14. Unger M, Wedel M, Tuzhilin A. Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture. Data Mining and Knowledge Discovery 2024;38(3):1069 View
  15. Ibragimov B, Mello-Thoms C. The Use of Machine Learning in Eye Tracking Studies in Medical Imaging: A Review. IEEE Journal of Biomedical and Health Informatics 2024;28(6):3597 View