Published on in Vol 11 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/40964, first published
.

Journals
- Lareyre F, Nasr B, Chaudhuri A, Di Lorenzo G, Carlier M, Raffort J. Comprehensive Review of Natural Language Processing (NLP) in Vascular Surgery. EJVES Vascular Forum 2023;60:57 View
- Cheligeer C, Wu G, Lee S, Pan J, Southern D, Martin E, Sapiro N, Eastwood C, Quan H, Xu Y. BERT-Based Neural Network for Inpatient Fall Detection From Electronic Medical Records: Retrospective Cohort Study. JMIR Medical Informatics 2024;12:e48995 View
- Kartsonis W, Pastena P, Hajagos J, Hirsch K, Gilotra K, Murundi S, Raiker A, de la Bastide C, Martinez C, Tassiopoulos A. Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports. Annals of Vascular Surgery 2025;110:95 View
- Chustecki M. Benefits and Risks of AI in Health Care: Narrative Review. Interactive Journal of Medical Research 2024;13:e53616 View
- Sajjadi S, Mohebbi A, Ehsani A, Marashi A, Azhdarimoghaddam A, Karami S, Karimi M, Sadeghi M, Firoozi K, Mohammad Zamani A, Rigi A, Nayebagha M, Asadi Anar M, Eini P, Salehi S, Rostami Ghezeljeh M. Identifying abdominal aortic aneurysm size and presence using Natural Language Processing of radiology reports: a systematic review and meta-analysis. Abdominal Radiology 2025;50(8):3885 View
- Chen Y, Zhang C, Bai R, Sun T, Ding W, Wang R. A review of medical text analysis: Theory and practice. Information Fusion 2025;119:103024 View
- Liang E, Pei S, Staibano P, van der Woerd B. Clinical applications of large language models in medicine and surgery: A scoping review. Journal of International Medical Research 2025;53(7) View
- Thompson D, Mofidi R. Natural Language Processing framework for identifying abdominal aortic aneurysm repairs using unstructured electronic health records. Scientific Reports 2025;15(1) View
- Sorin V, Collins J, Bratt A, Kusmirek J, Mugu V, Kline T, Butler C, Wood N, Cook C, Korfiatis P. Evaluating prompt and data perturbation sensitivity in large language models for radiology reports classification. JAMIA Open 2025;8(4) View