Department of Computer Science, New York University, New York, NY, USA.
AI Laboratory, Shenzhen Children's Hospital, Shenzhen, China.
J Child Psychol Psychiatry. 2023 Jun;64(6):966-967. doi: 10.1111/jcpp.13764. Epub 2023 Feb 19.
The commentary cites a study by Schulte-Rüther et al. (Journal of Child Psychology and Psychiatry, 2022) that proposed a machine learning model to predict a clinical best-estimate diagnosis of ASD when existing other co-occurring diagnoses. We discuss the valuable contribution of this work to developing a reliable computer-assisted diagnosis (CAD) system for ASD and point out that related research can be integrated with other multimodal machine learning methods. For future studies on developing the CAD system for ASD, we propose problems that need to be solved and potential research directions.
述评引用了 Schulte-Rüther 等人（《儿童心理学与精神病学杂志》，2022 年）的一项研究，该研究提出了一种机器学习模型，可在存在其他共病诊断的情况下预测 ASD 的临床最佳估计诊断。我们讨论了这项工作对开发 ASD 可靠计算机辅助诊断（CAD）系统的重要贡献，并指出相关研究可以与其他多模态机器学习方法相结合。对于开发 ASD CAD 系统的未来研究，我们提出了需要解决的问题和潜在的研究方向。
