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

Natural Language Processing (706) Artificial Intelligence (1421) Recruitment of Research Participants (305) Tools, Programs and Algorithms (275)

Published on in Vol 7, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15980, first published .
Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach

Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach

Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach

Authors of this article:

Irena Spasic1 Author Orcid Image ;   Dominik Krzeminski2 Author Orcid Image ;   Padraig Corcoran1 Author Orcid Image ;   Alexander Balinsky3 Author Orcid Image
Article Authors Cited by (12) Tweetations (7) Metrics

Journals

  1. Tarekegn A, Ricceri F, Costa G, Ferracin E, Giacobini M. Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches. JMIR Medical Informatics 2020;8(6):e16678 View
  2. Spasic I, Button K. Patient Triage by Topic Modeling of Referral Letters: Feasibility Study. JMIR Medical Informatics 2020;8(11):e21252 View
  3. Chen Z, Liu X, Hogan W, Shenkman E, Bian J. Applications of artificial intelligence in drug development using real-world data. Drug Discovery Today 2021;26(5):1256 View
  4. Chopard D, Treder M, Corcoran P, Ahmed N, Johnson C, Busse M, Spasic I. Text Mining of Adverse Events in Clinical Trials: Deep Learning Approach. JMIR Medical Informatics 2021;9(12):e28632 View
  5. Xiong Y, Peng W, Chen Q, Huang Z, Tang B. A Unified Machine Reading Comprehension Framework for Cohort Selection. IEEE Journal of Biomedical and Health Informatics 2022;26(1):379 View
  6. Idnay B, Dreisbach C, Weng C, Schnall R. A systematic review on natural language processing systems for eligibility prescreening in clinical research. Journal of the American Medical Informatics Association 2021;29(1):197 View
  7. Culié D, Schiappa R, Contu S, Scheller B, Villarme A, Dassonville O, Poissonnet G, Bozec A, Chamorey E. Validation and Improvement of a Convolutional Neural Network to Predict the Involved Pathology in a Head and Neck Surgery Cohort. International Journal of Environmental Research and Public Health 2022;19(19):12200 View
  8. Filimonov M, Chopard D, Spasić I, Wren J. Simulation and annotation of global acronyms. Bioinformatics 2022;38(11):3136 View
  9. Miok K, Corcoran P, Spasić I. The Value of Numbers in Clinical Text Classification. Machine Learning and Knowledge Extraction 2023;5(3):746 View
  10. Chopard D, Corcoran P, Spasić I. Word sense disambiguation of acronyms in clinical narratives. Frontiers in Digital Health 2024;6 View
  11. Mustafa A, Rahimi Azghadi M. Clustered Automated Machine Learning (CAML) model for clinical coding multi-label classification. International Journal of Machine Learning and Cybernetics 2024 View

Books/Policy Documents

  1. Scarpino I, Vallelunga R. Reference Module in Life Sciences. View