机器学习在婴幼儿孤独症谱系障碍早期筛查中的应用进展

Progress of machine learning in early screening of autism spectrum disorders among infants and toddlers

孤独症谱系障碍(autism spectrum disorder,ASD)起病于发育早期,对婴幼儿进行早期筛查是实现尽早干预和改善预后的关键。随着信息技术和医疗信息化的不断发展,机器学习在婴幼儿ASD早期筛查中的应用备受关注,并显示出其特有的优势。该文梳理机器学习在婴幼儿ASD早期筛查中的研究进展,旨在全面了解其发展态势,并剖析现有不足,为推动婴幼儿ASD早期筛查提供有益的借鉴。

The onset of autism spectrum disorder(ASD)is in early childhood.Early screening of ASD among infants and toddlers is the key to implement early intervention and improve prognosis.With the continuous development of information technology and medical informatization,the application of machine learning to early screening of ASD among infants and toddlers has attracted much attention and has shown its unique advantages.This paper reviews the research progress of machine learning in early screening of ASD among infants and toddlers,which aims to systematically understand the development trend and reflect the existing shortcomings,so as to provide reference for promoting early screening of ASD among infants and toddlers.