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Differentiating Surgeon Expertise Solely by Eye Movement Features

arXiv 2102.08155 ↗First posted 11 Feb 2021cs.CV cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 23 references that are in the map. First posted on arXiv 11 Feb 2021.

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References · 2

  1. 2020Deep semantic gaze embedding and scanpath comparison for expertise classification during OPT viewingcited by 17
  2. 2020Eye Movement Feature Classification for Soccer Goalkeeper Expertise Identification in Virtual Realitycited by 2

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