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

Theme Issue (2023): Generative & Multimodal AI in Digital Cardiovascular Medicine (6) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Machine Learning (1501) Coronary Heart Disease (81) Artificial Intelligence (1421) Computer-Aided Diagnosis (135) Advanced Data Analytics in eHealth (142)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51375, first published .
AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study

AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study

AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study

Authors of this article:

Enrico de Koning1 Author Orcid Image ;   Yvette van der Haas2 Author Orcid Image ;   Saguna Saguna2 Author Orcid Image ;   Esmee Stoop3 Author Orcid Image ;   Jan Bosch4 Author Orcid Image ;   Saskia Beeres1 Author Orcid Image ;   Martin Schalij1 Author Orcid Image ;   Mark Boogers1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Stalp J, Denecke A, Jentschke M, Hillemanns P, Klapdor R. Quality of ChatGPT-Generated Therapy Recommendations for Breast Cancer Treatment in Gynecology. Current Oncology 2024;31(7):3845 View