Abstract #3799

Application of machine learning with Tract-Based Spatial Statistics in the diagnosis of pediatric autism

Xiongpeng He¹, Xiaoan Zhang¹, Xin Zhao¹, Yongbin Sun², Pengfei Geng¹, and Kaiyu Wang³

¹Third Affiliated Hospital of Zhengzhou University, zhengzhou, China, ²Zhengzhou University People’s Hospital, zhengzhou, China, ³MR Research China, GE Healthcare, Beijing 100000, PR China, Beijing, China

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Diffusion/other diffusion imaging techniques, Tract-Based Spatial Statistics

Early and accurate diagnosis of pediatric autism was difficult for clinicians, which hindered the timely treatment of patients.This study aimed to explore the applicability of machine learning models of diffusion kurtosis imaging (DKI) based on Tract-Based Spatial Statistics to diagnose pediatric autism. Results showed that DKI parameter was potential for differentiating early autism from the normal. And the machine learning models can be used for early detection of pediatric autism with high accuracy and sensitivity.

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