# Differentiating Surgeon Expertise Solely by Eye Movement Features

arXiv: https://arxiv.org/abs/2102.08155 · HTML: https://mlsanity.com/paper/2102.08155/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 23 references that are in the map.
- First posted on arXiv 11 Feb 2021.

## Builds on (most cited first, 2 of 2)

- [Deep semantic gaze embedding and scanpath comparison for expertise classification during OPT viewing](https://mlsanity.com/paper/2003.13987/) (2020)
- [Eye Movement Feature Classification for Soccer Goalkeeper Expertise Identification in Virtual Reality](https://mlsanity.com/paper/2009.11676/) (2020)

## 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.