Accessibility settings

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

Formative Evaluation of Digital Health Interventions (3579) Clinical Informatics (1494) Clinical Information and Decision Making (2149) mHealth in a Clinical Setting (804) Machine Learning (2306) Novel Sensors and Data Acquisition Methods in Cardiology (239) Stroke (277) E-Health / Health Services Research and New Models of Care (825)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54009, first published .
Person using a smartphone app to assess stroke symptoms: fluctuating, transient, or resolved.

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study

Authors of this article:

Ayman Hassan1, 2, 3 Author Orcid Image ;   Rachid Benlamri4 Author Orcid Image ;   Trina Diner1 Author Orcid Image ;   Keli Cristofaro1 Author Orcid Image ;   Lucas Dillistone5 Author Orcid Image ;   Hajar Khallouki5 Author Orcid Image ;   Mahvareh Ahghari6 Author Orcid Image ;   Shalyn Littlefield2 Author Orcid Image ;   Rabail Siddiqui2 Author Orcid Image ;   Russell MacDonald6 Author Orcid Image ;   David W Savage1, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics Author Video

Journals

  1. Heo J. Application of Artificial Intelligence in Acute Ischemic Stroke: A Scoping Review. Neurointervention 2025;20(1):4 View
  2. Sorkin G, Caffes N, Shank J, Hershey J, Knaub D, Krebs J, Niazi M. Current State of the Clinical Applications of Artificial Intelligence in Stroke: A Literature Review. Brain Sciences 2026;16(2):173 View
  3. Miles J, Brady M, Smith L, Cotterill C, Levey C. Use of artificial intelligence in the out-of-hospital care settings: a scoping review. BMJ Digital Health & AI 2026;2(1):e000035 View