自闭症
医学诊断
计算机科学
自闭症谱系障碍
人工智能
心理学
机器学习
医学
发展心理学
病理
作者
Dinghuang Zhang,Dalin Zhou,Honghai Liu
标识
DOI:10.1109/icmlc58545.2023.10327994
摘要
Given the current increasing prevalence of autism, expensive and time-consuming manual diagnosis is highly detrimental to the management of the condition. With the development of computer-based methods of human behavioural analysis, these methods are expected to provide more accurate, objective and reproducible methods of early screening and diagnosis of autism. To advance the field of behavioural quantification in autism research, this study utilises human skeletal behavioural data from publicly available autism datasets and ADOS scores from clinical professionals in a first attempt to build deep neural networks that can predict ADOS scores from behavioural data using the AQA approach. This paper finds a moderately correlated between the ground truth ADOS score and the predicted ADOS score, it reveals the potential use of the AQA method in ASD diagnoses.
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