Published on in Vol 24, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40387, first published .
Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial

Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial

Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial

Journals

  1. Saragosa M, Zagrodney K, Rabeenthira P, King E, McKay S. How Might We Have Known? Using Administrative Data to Predict 30-Day Hospital Readmission in Clients Receiving Home Care Services from 2018 to 2021. Health Services Insights 2023;16 View
  2. Arnaud E, Petitprez E, Ammirati C, Nemitz B, Dequen G, Gignon M, Ghazali D. L’intelligence artificielle dans les structures d’urgences : place de la formation et de la garantie humaine. Annales françaises de médecine d’urgence 2023;13(3):169 View
  3. Olender R, Roy S, Nishtala P. Application of machine learning approaches in predicting clinical outcomes in older adults – a systematic review and meta-analysis. BMC Geriatrics 2023;23(1) View