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

Clinical Information and Decision Making (1598) Decision Support for Health Professionals (1319) Natural Language Processing (782) Machine Learning (1677)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43153, first published .
Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation

Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation

Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation

Authors of this article:

Zhi-Geng Jin1 Author Orcid Image ;   Hui Zhang1 Author Orcid Image ;   Mei-Hui Tai2 Author Orcid Image ;   Ying Yang3 Author Orcid Image ;   Yuan Yao4 Author Orcid Image ;   Yu-Tao Guo1 Author Orcid Image
Article Authors Cited by (4) Tweetations (4) Metrics

Journals

  1. Reyes Gil M, Pantanowitz J, Rashidi H. Venous thromboembolism in the era of machine learning and artificial intelligence in medicine. Thrombosis Research 2024;242:109121 View
  2. 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
  3. Naser A, Vyas R, Morgan A, Kalaiger A, Kharawala A, Nagraj S, Agarwal R, Maliha M, Mangeshkar S, Singh N, Satish V, Mathai S, Palaiodimos L, Faillace R. Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review. Diagnostics 2025;15(7):889 View

Books/Policy Documents

  1. Laabidi A, Aissaoui M, Madani M. Proceedings of Ninth International Congress on Information and Communication Technology. View