Differentiating Surgeon Expertise Solely by Eye Movement Features
Benedikt Werner Hosp, Myat Su Yin, Peter Haddawy, Paphon Sa-ngasoongsong, Enkelejda Kasneci · arXiv (Cornell University) · 2021
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.