Transparent deep learning to identify autism spectrum disorders (ASD) in EHR using clinical notes.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: May 20, 2024

Abstract

OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are transparent and in line with clinical, diagnostic rules. We demonstrate our approach for autism spectrum disorders (ASD), a neurodevelopmental condition with increasing prevalence.

Authors

  • Gondy Leroy
    University of Arizona, Tucson, AZ, United States.
  • Jennifer G Andrews
    Department of Pediatrics, The University of Arizona, Tucson, AZ 85621, United States.
  • Madison KeAlohi-Preece
    Department of Psychology, The University of Arizona, Tucson, AZ 85621, United States.
  • Ajay Jaswani
    Department of Management Information Systems, The University of Arizona, Tucson, AZ 85621, United States.
  • Hyunju Song
    Department of Computer Science, The University of Arizona, Tucson, AZ 85621, United States.
  • Maureen Kelly Galindo
    University of Arizona, Tucson, Arizona.
  • Sydney A Rice
    Department of Pediatrics, The University of Arizona, Tucson, AZ 85621, United States.

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