Developments in computer science in recent years are moving into hospitals. Surgeons are faced with ever new technical challenges. Visual perception plays a key role in most of these. Diagnostic and training models are needed to optimize the training of young surgeons. In this study, we present a model for classifying experts, 4th-year residents and 3rd-year residents, using only eye movements. We show a model that uses a minimal set of features and still achieve a robust accuracy of 76.46 % to classify eye movements into the correct class. Likewise, in this study, we address the evolutionary steps of visual perception between three expertise classes, forming a first step towards a diagnostic model for expertise.
@article{arxiv.2102.08155,
title = {Differentiating Surgeon Expertise Solely by Eye Movement Features},
author = {Benedikt Hosp and Myat Su Yin and Peter Haddawy and Paphon Sa-Ngasoongsong and Enkelejda Kasneci},
journal= {arXiv preprint arXiv:2102.08155},
year = {2021}
}