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

Natural Language Processing (692) Artificial Intelligence (1371) Electronic Health Records (1053) Machine Learning (1465)

Published on in Vol 9, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17934, first published .
Hybrid Deep Learning for Medication-Related Information Extraction From Clinical Texts in French: MedExt Algorithm Development Study

Hybrid Deep Learning for Medication-Related Information Extraction From Clinical Texts in French: MedExt Algorithm Development Study

Hybrid Deep Learning for Medication-Related Information Extraction From Clinical Texts in French: MedExt Algorithm Development Study

Authors of this article:

Jordan Jouffroy1, 2 Author Orcid Image ;   Sarah F Feldman1, 2 Author Orcid Image ;   Ivan Lerner1, 2 Author Orcid Image ;   Bastien Rance2, 3 Author Orcid Image ;   Anita Burgun1, 2 Author Orcid Image ;   Antoine Neuraz1, 2 Author Orcid Image
Article Authors Cited by (16) Tweetations (4) Metrics

Journals

  1. Hoertel N, Sánchez-Rico M, de la Muela P, Abellán M, Blanco C, Leboyer M, Cougoule C, Gulbins E, Kornhuber J, Carpinteiro A, Becker K, Vernet R, Beeker N, Neuraz A, Alvarado J, Herrera-Morueco J, Airagnes G, Lemogne C, Limosin F, Ancel P, Bauchet A, Benoit V, Bernaux M, Bellamine A, Bey R, Bourmaud A, Breant S, Burgun A, Carrat F, Caucheteux C, Champ J, Cormont S, Daniel C, Dubiel J, Ducloas C, Esteve L, Frank M, Garcelon N, Gramfort A, Griffon N, Grisel O, Guilbaud M, Hassen-Khodja C, Hemery F, Hilka M, Jannot A, Lambert J, Layese R, Leblanc J, Lebouter L, Lemaitre G, Leprovost D, Lerner I, Sallah K, Maire A, Mamzer M, Martel P, Mensch A, Moreau T, Orlova N, Paris N, Rance B, Ravera H, Rozes A, Salamanca E, Sandrin A, Serre P, Tannier X, Treluyer J, Van Gysel D, Varoquaux G, Vie J, Wack M, Wajsburt P, Wassermann D, Zapletal E. Risk of Death in Individuals Hospitalized for COVID-19 With and Without Psychiatric Disorders: An Observational Multicenter Study in France. Biological Psychiatry Global Open Science 2023;3(1):56 View
  2. Bannour N, Wajsbürt P, Rance B, Tannier X, Névéol A. Privacy-preserving mimic models for clinical named entity recognition in French. Journal of Biomedical Informatics 2022;130:104073 View
  3. Campillos-Llanos L. MedLexSp – a medical lexicon for Spanish medical natural language processing. Journal of Biomedical Semantics 2023;14(1) View
  4. de Oliveira J, da Costa C, Antunes R. Data structuring of electronic health records: a systematic review. Health and Technology 2021;11(6):1219 View
  5. Bazoge A, Morin E, Daille B, Gourraud P. Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review. JMIR Medical Informatics 2023;11:e42477 View
  6. Pourcher V, Tubach F, Rozes A, Boussouar S, Estellat C. Outcomes of coronavirus disease 2019-related hospitalization among people with HIV: historical cohort from the Greater Paris area multicenter hospital data warehouse. AIDS 2023;37(12):1915 View
  7. Wang T, Codling D, Bhugra D, Msosa Y, Broadbent M, Patel R, Roberts A, McGuire P, Stewart R, Dobson R, Harland R. Unraveling ethnic disparities in antipsychotic prescribing among patients with psychosis: A retrospective cohort study based on electronic clinical records. Schizophrenia Research 2023;260:168 View
  8. Amiri Z, Heidari A, Darbandi M, Yazdani Y, Jafari Navimipour N, Esmaeilpour M, Sheykhi F, Unal M. The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors. Sustainability 2023;15(16):12406 View
  9. Modi S, Kasmiran K, Mohd Sharef N, Sharum M. Extracting adverse drug events from clinical Notes: A systematic review of approaches used. Journal of Biomedical Informatics 2024;151:104603 View
  10. Petit-Jean T, Gérardin C, Berthelot E, Chatellier G, Frank M, Tannier X, Kempf E, Bey R. Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions. Journal of the American Medical Informatics Association 2024;31(6):1280 View
  11. Barruel D, Hilbey J, Charlet J, Chaumette B, Krebs M, Dauriac-Le Masson V. Predicting treatment resistance in schizophrenia patients: Machine learning highlights the role of early pathophysiologic features. Schizophrenia Research 2024;270:1 View
  12. Wen A, Wang L, He H, Fu S, Liu S, Hanauer D, Harris D, Kavuluru R, Zhang R, Natarajan K, Pavinkurve N, Hajagos J, Rajupet S, Lingam V, Saltz M, Elowsky C, Moffitt R, Koraishy F, Palchuk M, Donovan J, Lingrey L, Stone-DerHagopian G, Miller R, Williams A, Leese P, Kovach P, Pfaff E, Zemmel M, Pates R, Guthe N, Haendel M, Chute C, Liu H. A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation. JMIR Medical Informatics 2024;12:e49997 View
  13. Nunes M, Bone J, Ferreira J, Elvas L. Health Care Language Models and Their Fine-Tuning for Information Extraction: Scoping Review. JMIR Medical Informatics 2024;12:e60164 View

Books/Policy Documents

  1. Guan M. Machine Learning and Deep Learning in Computational Toxicology. View