The application of machine learning in combination with eye-tracking technology in the early identification of autism
10.3760/cma.j.cn113661-20231117-00217
- VernacularTitle:机器学习联合眼动注视模式在孤独症早期诊断中的应用
- Author:
Tianyi CHANG
1
;
Fanchao MENG
1
;
Yin TIAN
1
;
Xu CHEN
1
;
Yi ZHENG
1
Author Information
1. 首都医科大学附属北京安定医院，国家精神疾病医学中心，国家精神心理疾病临床医学研究中心，北京 100088
- Publication Type:Journal Article
- Keywords:
Autistic disorder;
Diagnosis;
Classification;
Machine learning;
Eye-tracking
- From:
Chinese Journal of Psychiatry
2024;57(9):623-628
- CountryChina
- Language:Chinese
-
Abstract:
Early and objective assessment, as well as early intervention, are of particular importance for autism spectrum disorder (ASD) to improve the long-term outcome. However, due to a lack of objective biomarkers, the current assessment of ASD depends mainly on limited behavioral observation. Recent advancements in software and hardware multimedia technologies provide new ways to identify ASD early. Evidence supports that the combination of machine learning with eye-tracking technology is expected to be a useful tool for the early and objective diagnosis of ASD. The current study reviewed the research on the combination of machine learning with eye-tracking technology for the identification of ASD. The limitations and future directions have also been proposed.
