TY - JOUR A2 - Juhola, Martti AU - Andrade, Evandro AU - Portela, Samuel AU - Pinheiro, Plácido Rogério AU - Nunes, Luciano Comin AU - Filho, Marum Simão AU - Costa, Wagner Silva AU - Pinheiro，Mirian Caliope Dantas PY - 2021 DA - 2021/03/31 TI - A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis SP - 1628959 VL - 2021 AB -自闭症谱系障碍是一种精神疾病，折磨着全世界数百万人。据估计，每160名儿童中就有1人患有自闭症，而男孩的患病率是男孩的5倍。检测症状的协议多种多样。然而，以下是最常用的:美国精神病学协会的《精神障碍诊断与统计手册第5版》(DSM-5);修订的自闭症诊断观察表(ADOS-R);自闭症诊断访谈(ADI);国际疾病分类第10版(ICD-10)，由世界卫生组织(WHO)出版，在巴西由统一卫生系统(SUS)采用。机器学习模型的应用有助于使自闭症谱系障碍的诊断过程更加精确，在许多情况下，减少了评估所需的标准数量，表明了一种形式的属性工程(特征工程)效率。本文提出了一种基于机器学习算法组合的混合方法，用于发现与基于语言决策分析的多准则决策支持方法相关的知识和概念，以细化结果。 Therefore, the study has the general objective of evaluating how the mentioned hybrid methodology proposal can make the protocol derived from ICD-10 more efficient, providing agility to diagnosing Autism Spectrum Disorder by observing a minor symptom. The study database covers thousands of cases of people who, once diagnosed, obtained government assistance in Brazil. SN - 1748-670X UR - https://doi.org/10.1155/2021/1628959 DO - 10.1155/2021/1628959 JF - Computational and Mathematical Methods in Medicine PB - Hindawi KW - ER -