Performance Prediction of Surgeon with Eye-Gaze Data for Robot-Assisted-Surgery

被引：0

作者：

Teksin, Murat ^{[1
,2
]}

Ayata, Deger ^{[1
,2
]}

机构：

[1] TUSAS, Ankara, Turkiye

[2] ITU Fac Elect & Elect Engn, Istanbul, Turkiye

来源：

32ND IEEE SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU 2024 | 2024年

关键词：

machine learning; regression; prediction; artificial for healthcare; robot assisted surgery; eye-tracker;

D O I：

10.1109/SIU61531.2024.10600939

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Robot assisted surgery is quite useful method for medical operations. To use this method properly, evaluation of surgeon with low experience has critical significance. Currently, evaluation is made by simulation programs that specified for robot assisted surgery or result of scoring with a survey made by expert surgeon who tracks all the session. Aim of this study is assessment of surgeons in real life robot-assisted operations with eye-tracker device without an evaluator. To make this evaluation, output with constructed regression models with derived features from an open source data that has been collecting during robot-assisted-surgery simulation is compared with score produced by simulation. Mean of root mean squared error of Xgboost that has 0.124 value and R2 score as 0.456 value were obtained for best model output.

引用

页数：4

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