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

Artificial Intelligence (2246) JMIR Theme Issue: COVID-19 Special Issue (2559) Clinical Informatics (1376) Clinical Information and Decision Making (2001) Electronic Health Records (1351) New Methods (1152) Ontologies, Classifications, and Coding (337)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49944, first published .
A Natural Language Processing Model for COVID-19 Detection Based on Dutch General Practice Electronic Health Records by Using Bidirectional Encoder Representations From Transformers: Development and Validation Study

A Natural Language Processing Model for COVID-19 Detection Based on Dutch General Practice Electronic Health Records by Using Bidirectional Encoder Representations From Transformers: Development and Validation Study

A Natural Language Processing Model for COVID-19 Detection Based on Dutch General Practice Electronic Health Records by Using Bidirectional Encoder Representations From Transformers: Development and Validation Study

Authors of this article:

Maarten Homburg1 Author Orcid Image ;   Eline Meijer1, 2 Author Orcid Image ;   Matthijs Berends1, 3, 4 Author Orcid Image ;   Thijmen Kupers1, 2 Author Orcid Image ;   Tim Olde Hartman5 Author Orcid Image ;   Jean Muris6 Author Orcid Image ;   Evelien de Schepper7 Author Orcid Image ;   Premysl Velek7 Author Orcid Image ;   Jeroen Kuiper8 Author Orcid Image ;   Marjolein Berger1 Author Orcid Image ;   Lilian Peters1, 2, 9 Author Orcid Image
Article Authors Cited by (11) Tweetations (6) Metrics

Journals

  1. Chen S, Yu J, Chamouni S, Wang Y, Li Y. Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions. BMC Medicine 2024;22(1) View
  2. Han Y, Lam J, Li V, Crowcroft J. Interpretable AI-driven causal inference to uncover the time-varying effects of PM2.5 and public health interventions on COVID-19 infection rates. Humanities and Social Sciences Communications 2024;11(1) View
  3. van Essen M, Twickler R, Weesie Y, Arslan I, Groenhof F, Peters L, Bos I, Verheij R. Implications of Data Extraction and Processing of Electronic Health Records for Epidemiological Research: Observational Study. Journal of Medical Internet Research 2025;27:e64628 View
  4. Veldman C, Van Gijssel E, Van Rooij A, Buitenhuis L, Van Den Berg J, Blanker M. Hasselt Corona Impact Study: Impact of COVID-19 on healthcare seeking in a small Dutch town. npj Primary Care Respiratory Medicine 2025;35(1) View
  5. Kim J, Chen M, Rezaei S, Ramirez-Posada M, Caswell-Jin J, Kurian A, Riaz F, Sarin K, Tang J, Asch S, Linos E. Patient-Centered Research Through Artificial Intelligence to Identify Priorities in Cancer Care. JAMA Oncology 2025;11(6):630 View
  6. Geersing G, de Wit N, Thompson M. Generative artificial intelligence for general practice; new potential ahead, but are we ready?. European Journal of General Practice 2025;31(1) View
  7. Alkalbani A, Alrawahi A, Salah A, Haghighi V, Zhang Y, Alkindi S, Sheng Q. A Systematic Review of Large Language Models in Medical Specialties: Applications, Challenges and Future Directions. Information 2025;16(6):489 View
  8. Li J, Tseng Y, Chen S, Chen K. Artificial Intelligence in Infection Surveillance: Data Integration, Applications and Future Directions. Biomedical Journal 2025:100929 View
  9. Homburg M, Danoe G, Berger M, Hartman T, Muris J, Voss A, Hamprecht A, Brilman M, Peters L, Berends M. AI-driven early infectious disease detection in Dutch primary care using BERT and ERNIE. npj Digital Medicine 2025;9(1) View
  10. Hunik L, Uijen A, Kueper J, Terry A, olde Hartman T, van Laarhoven T, Schers H. The role and utility of artificial intelligence and machine learning for diagnostic prediction in general practice. European Journal of General Practice 2026;32(1) View

Books/Policy Documents

  1. Mandal K, Saxena K. Smart Computing Paradigms: Sustainable Computing. View