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

Artificial Intelligence (2129) Clinical Information and Decision Making (1915) Machine Learning (2076) Data Science (357) Pulmonology, COPD (195) Respiratory Medicine (157) Secondary Use of Clinical Data for Research and Surveillance (474)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48595, first published .
Early Detection of Pulmonary Embolism in a General Patient Population Immediately Upon Hospital Admission Using Machine Learning to Identify New, Unidentified Risk Factors: Model Development Study

Early Detection of Pulmonary Embolism in a General Patient Population Immediately Upon Hospital Admission Using Machine Learning to Identify New, Unidentified Risk Factors: Model Development Study

Early Detection of Pulmonary Embolism in a General Patient Population Immediately Upon Hospital Admission Using Machine Learning to Identify New, Unidentified Risk Factors: Model Development Study

Authors of this article:

Ori Ben Yehuda1 Author Orcid Image ;   Edward Itelman2, 3 Author Orcid Image ;   Adva Vaisman2 Author Orcid Image ;   Gad Segal2 Author Orcid Image ;   Boaz Lerner1 Author Orcid Image
Article Authors Cited by (7) Tweetations (2) Metrics

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  3. Li Y, Zhang L, Liu H, Li Y, Liu Z. Research progress of artificial intelligence and machine learning in pulmonary embolism. Frontiers in Medicine 2025;12 View
  4. Gong M, Jiang R, Guo K, He X, Gu J. A predictive model for early detection of concomitant pulmonary embolism in patients with deep vein thrombosis immediately upon hospital admission. Journal of Vascular Surgery: Venous and Lymphatic Disorders 2025;13(6):102299 View
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  6. Hack S, Attal R, Elazar D, Alon Y, Meyuchas R, Livne A, Madgar O, Saban M. Cautionary lessons from real-world testing of GPT-4.1 AI for pediatric foreign body aspiration. European Archives of Oto-Rhino-Laryngology 2025 View

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  1. Kumar R, Gautam P, Kumar N, Rawat A, Kamboj N, Mehra P. 2024 4th International Conference on Innovative Sustainable Computational Technologies (CISCT). Antimicrobial Resistance Pathogen Detection by AI and ML View