Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67837, first published .
Natural Language Processing and ICD-10 Coding for Detecting Bleeding Events in Discharge Summaries: Comparative Cross-Sectional Study

Natural Language Processing and ICD-10 Coding for Detecting Bleeding Events in Discharge Summaries: Comparative Cross-Sectional Study

Natural Language Processing and ICD-10 Coding for Detecting Bleeding Events in Discharge Summaries: Comparative Cross-Sectional Study

Frederic Gaspar   1, 2 * , PhD ;   Mehdi Zayene   3 , MSc ;   Claire Coumau   1, 2, 4 , MSc ;   Elliott Bertrand   3 , MSc ;   Marie Bettex   5 , MD ;   Marie Annick Le Pogam   5 * , MD, PhD ;   Chantal Csajka   2, 4 * , PhD

1 Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne, Switzerland

2 School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland

3 Effixis SA, Lausanne, Switzerland

4 Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva and Lausanne, Switzerland

5 Department of Epidemiology and Health Systems, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland

*these authors contributed equally

Corresponding Author:

  • Frederic Gaspar, PhD
  • Center for Research and Innovation in Clinical Pharmaceutical Sciences
  • Rue du Bugnon 19
  • Lausanne 1011
  • Switzerland
  • Phone: 41 763306834
  • Email: frederic.gaspar@chuv.ch