Semi-supervised clustering for neuro-subtyping of autism spectrum disorder

Zihao Li; Yaping Wang; Xiujuan Geng

doi:10.1117/12.2654125

3 April 2023 Semi-supervised clustering for neuro-subtyping of autism spectrum disorder

Zihao Li, Yaping Wang, Xiujuan Geng

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124642Q (2023) https://doi.org/10.1117/12.2654125
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

This is the first study to conduct neuro-subtyping of autism spectrum disorder with a semi-supervised clustering method HYDRA. With the use of functional connectivity data from a large cohort of ASD, ABIDE, a multi-scale dimension-reduction method OPNNMF was first conducted to get a more robust and representable feature space with reduced dimensions. A three-layer procedure was conducted to obtain the optimal clustering in terms of better validity and reliability indices resulting two distinct clusters. By comparing with unsupervised clustering, the semi-supervised method showed more distinct connectivity patterns between clusters. Heterogenous brain-behavior relationships under various brain networks were observed across clusters indicating potential usage of ASD neuro-subtyping to detect reliable neuro-biomarkers assisting precise diagnosis and treatment in the future.

Citation Download Citation

Zihao Li, Yaping Wang, and Xiujuan Geng "Semi-supervised clustering for neuro-subtyping of autism spectrum disorder", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124642Q (3 April 2023); https://doi.org/10.1117/12.2654125

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