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

Formative Evaluation of Digital Health Interventions (3347) Clinical Information and Decision Making (2004) mHealth in a Clinical Setting (758) Clinical Informatics (1377) E-Health / Health Services Research and New Models of Care (758) Machine Learning (2166) Stroke (254) Novel Sensors and Data Acquisition Methods in Cardiology (232)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54009, first published .
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

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 (2) 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