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This paper is in the following e-collection/theme issue:

Scoping Review Protocols (575) Attention Deficit Disorder (ADD/ADHD) (156) Diagnostic Tools in Mental Health (454) Clinical Mental Health Informatics (149) Reviews in AI (205) Applications of AI (1069)

Published on in Vol 15 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/99551, first published .
Doctor analyzing brain MRI scans on a computer monitor in a medical facility.

Artificial Intelligence, Machine Learning, and Deep Learning Approaches for Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for a Scoping Review

Artificial Intelligence, Machine Learning, and Deep Learning Approaches for Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for a Scoping Review

Authors of this article:

Benedict Onochie Ibe1 Author Orcid Image ;   Amir Aly1 Author Orcid Image ;   Shaymaa S Al-Juboori1 Author Orcid Image ;   Emmanuel Ifeachor1 Author Orcid Image ;   Rohit Shankar1, 2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Benedict Onochie Ibe   1 , MSc ;   Amir Aly   1 , PhD ;   Shaymaa S Al-Juboori   1 , PhD ;   Emmanuel Ifeachor   1 , PhD ;   Rohit Shankar   1, 2 , FRCPsych

1 School of Engineering, Computing and Mathematics, University of Plymouth, Devon, England, United Kingdom

2 Cornwall Intellectual Disability Equitable Research (CIDER), Plymouth, Devon, United Kingdom

Corresponding Author:

  • Benedict Onochie Ibe, MSc
  • School of Engineering, Computing and Mathematics
  • University of Plymouth
  • Drake Circus, Plymouth
  • Devon, England PL4 8AA
  • United Kingdom
  • Phone: 44 07476836637
  • Email: benedict.ibe@plymouth.ac.uk