Commentary: Machine learning for autism spectrum disorder diagnosis - challenges and opportunities - a commentary on
Xu Cao1,2,3, Jianguo Cao2,4
1Department of Computer Science, New York University, New York, NY, USA.
Abstract:
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.
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