Constructing a predictive model for children with autism spectrum disorder based on whole brain magnetic resonance radiomics: a machine learning study.

Journal: AJNR. American journal of neuroradiology
Published Date: Jul 28, 2025

Abstract

BACKGROUND AND PURPOSE: Autism spectrum disorder (ASD) diagnosis remains challenging and could benefit from objective imaging-based approaches. This study aimed to construct a prediction model using whole-brain imaging radiomics and machine learning to identify children with ASD.

Authors

  • Xi Chen
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Jiaxuan Peng
    Jinzhou Medical University, Jinzhou, Liaoning Province, China.
  • Zihan Zhang
  • Qiaowei Song
    Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Dongxue Li
    College of Civil Traffic & Transportation, Chongqing Jiaotong University, Chongqing, 400074, China.
  • Gongyong Zhai
    Jiaxuan Peng, Zihan Zhang, Qiaowei Song, Dongxue Li, Gongyong Zhai, Wanyun Fu, Zhenyu Shu, From the Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou City, Zhejiang Province, China.
  • Wanyun Fu
    Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.; The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310053 Zhejiang, China.
  • Zhenyu Shu
    Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou.

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