Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36877, first published .
Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Journals

  1. Jin Z, Zhang H, Tai M, Yang Y, Yao Y, Guo Y. Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation. Journal of Medical Internet Research 2023;25:e43153 View
  2. Wendelboe A, Weitz J. Global Health Burden of Venous Thromboembolism. Arteriosclerosis, Thrombosis, and Vascular Biology 2024;44(5):1007 View
  3. Lam B, Chrysafi P, Chiasakul T, Khosla H, Karagkouni D, McNichol M, Adamski A, Reyes N, Abe K, Mantha S, Vlachos I, Zwicker J, Patell R. Machine learning natural language processing for identifying venous thromboembolism: systematic review and meta-analysis. Blood Advances 2024;8(12):2991 View