The prevalence of neurodevelopment disorders (NDDs) among children has been on the rise. This has affected the health and social life of children. This condition has also imposed a huge economic burden on families and health care systems. Currently, it is difficult to perform early diagnosis of NDDs, which results in delayed intervention. For this reason, patients with NDDs have a prognosis. In recent years, machine learning (ML) technology, which integrates artificial intelligence technology and medicine, has been applied in the early detection and prediction of diseases based on data mining. This paper reviews the progress made in the application of ML in the diagnosis and treatment of NDDs in children based on supervised and unsupervised learning tools. The data reviewed here provide new perspectives on early diagnosis and treatment of NDDs.

儿童中神经发育障碍（NDD）的患病率一直在上升。这影响了儿童的健康和社会生活。这种情况也给家庭和医疗保健系统带来了巨大的经济负担。目前，难以对NDDs进行早期诊断，导致干预延迟。因此，患有NDDs的患者有预后。近年来，将人工智能技术与医学相结合的机器学习（ML）技术应用于基于数据挖掘的疾病早期检测和预测。本文回顾了基于有监督和无监督学习工具的 ML 在儿童 NDD 诊断和治疗中的应用进展。这里审查的数据为NDDs的早期诊断和治疗提供了新的视角。