Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network.

Journal: International journal of medical informatics
Published Date: Nov 16, 2024

Abstract

BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social interactions and behavior. Accurate and early diagnosis of ASD is still challenging even with the improvements in neuroimaging technology and machine learning algorithms. It's challenging because of the wide range of symptoms, delayed appearance of symptoms, and the subjective nature of diagnosis. In this study, the aim is to enhance ASD recognition by focusing on brain subcortical regions, which are critical for understanding ASD pathology.

Authors

  • Anas Abu-Doleh
    Biomedical Systems and Informatics Engineering Department, Yarmouk University, Irbid 21163, Jordan. Electronic address: anas.abudoleh@yu.edu.jo.
  • Isam F Abu-Qasmieh
    Biomedical Systems and Informatics Engineering Department, Yarmouk University, Irbid 21163, Jordan.
  • Hiam H Al-Quran
    Biomedical Systems and Informatics Engineering Department, Yarmouk University, Irbid 21163, Jordan.
  • Ihssan S Masad
    Biomedical Systems and Informatics Engineering Department, Yarmouk University, Irbid 21163, Jordan; Department of Electrical and Computer Engineering, Gulf University for Science and Technology (GUST), Hawally 32093, Kuwait.
  • Lamis R Banyissa
    Biomedical Systems and Informatics Engineering Department, Yarmouk University, Irbid 21163, Jordan.
  • Marwa Alhaj Ahmad
    Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates.

Keywords

External Resources

Popular Topics
Recent Journals