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

Reviews in Medical Informatics (96) Natural Language Processing (777) Big Data (274) Electronic Health Records (1145) Secondary Use of Clinical Data for Research and Surveillance (405) Machine Learning (1667) Advanced Data Analytics in eHealth (159)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42477, first published .
Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review

Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review

Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review

Authors of this article:

Adrien Bazoge1, 2 Author Orcid Image ;   Emmanuel Morin1 Author Orcid Image ;   Béatrice Daille1 Author Orcid Image ;   Pierre-Antoine Gourraud2, 3 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

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  2. Zaribafzadeh H, Henson J, Chan N, Rogers U, Webster W, Schappe T, Li F, Matsouaka R, Kirk A, Henao R, McElroy L. Development of a natural language processing algorithm to extract social determinants of health from clinician notes. American Journal of Transplantation 2025 View
  3. Guimarães P, Carvalho M, Ruiz J. A computational framework for extracting biological insights from SRA cancer data. Scientific Reports 2025;15(1) View
  4. Wiens M, Verone‐Boyle A, Henscheid N, Podichetty J, Burton J. A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications. Clinical and Translational Science 2025;18(3) View