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自闭症筛查与诊断的客观评估工具——一项系统性综述
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Abstract:
目前对自闭症的筛查与诊断往往基于需要主观评级的标准化访谈或量表，这样的评估方式往往依赖于经验丰富的专业人员，而且具有较强的主观性，耗时耗力，不便普及。较少研究对筛选ASD群体的客观评估工具进行综述。因此，本综述总结了近五年用于自闭症筛查与诊断的客观评估工具及相关可量化的指标，根据研究方法主要总结为以下四类：(1) 基于计算机化测验的行为学研究；(2) 基于眼动追踪技术的研究；(3) 基于脑成像技术的研究；(4) 基于机器学习分类算法的研究，以期为ASD群体的客观筛查方式提供一定的参考依据。
At present, the screening and diagnosis of autism is often based on standardized interviews or scales that require subjective ratings, which often rely on experienced professionals, and are highly subjective, time-consuming, and inconvenient to popularize. Few studies reviewed objective assessment tools for screening populations with ASD. Therefore, this review summarizes the objective assessment tools and related quantifiable indicators used for autism screening and diagnosis in the past five years, which are mainly summarized into the following four categories according to the research methods: (1) Behavioral research based on computerized tests; (2) Research based on eye tracking technology; (3) Research based on brain imaging technology; (4) Research based on machine learning classification algorithm, in order to provide a certain reference for the objective screening method of ASD population.
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