A reliable diagnosis of autism spectrum disorder (ASD) is difficult to make until after toddlerhood. Detection in an earlier age enables early intervention, which is typically more effective. Recent studies of the development of brain and behavior in infants and toddlers have provided important insights in the diagnosis of autism. This extensive review focuses on published studies of predicting the diagnosis of autism during infancy and toddlerhood younger than 3 years using behavioral and neuroimaging approaches. After screening a total of 782 papers, 17 neuroimaging and 43 behavioral studies were reviewed. The features for prediction consist of behavioral measures using screening tools, observational and experimental methods, brain volumetric measures, and neural functional activation and connectivity patterns. The classification approaches include logistic regression, linear discriminant function, decision trees, support vector machine, and deep learning based methods. Prediction performance has large variance across different studies. For behavioral studies, the sensitivity varies from 20% to 100%, and specificity ranges from 48% to 100%. The accuracy rates range from 61% to 94% in neuroimaging studies. Possible factors contributing to this inconsistency may be partially due to the heterogeneity of ASD, different targeted populations (i.e., high-risk group for ASD and general population), age when the features were collected, and validation procedures. The translation to clinical practice requires extensive further research including external validation with large sample size and optimized feature selection. The use of multi-modal features, e.g., combination of neuroimaging and behavior, is worth further investigation to improve the prediction accuracy.

直到学步后才能对自闭症谱系障碍（ASD）做出可靠的诊断。在较早的年龄进行检测可以及早介入，这通常更有效。最近对婴幼儿大脑发育和行为发展的研究为自闭症的诊断提供了重要的见识。这篇广泛的综述侧重于已发表的研究，这些研究使用行为和神经影像学方法预测了3岁以下的婴儿和幼儿期自闭症的诊断。筛选了782篇论文后，对17篇神经影像学和43项行为研究进行了综述。预测功能包括使用筛选工具的行为测度，观察和实验方法，脑容量测度以及神经功能激活和连通性模式。分类方法包括逻辑回归，线性判别函数，决策树，支持向量机和基于深度学习的方法。不同研究之间的预测表现差异很大。对于行为研究，敏感性从20％到100％不等，特异性从48％到100％不等。在神经影像学研究中，准确率从61％到94％不等。导致这种不一致的可能因素可能部分是由于ASD的异质性，不同的目标人群（即，ASD和一般人群的高风险人群），收集特征的年龄以及验证程序。转换为临床实践需要广泛的进一步研究，包括具有大样本量和优化特征选择的外部验证。使用多模式功能，例如