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

Natural Language Processing (644) Artificial Intelligence (1198) Recruitment of Research Participants (280) Tools, Programs and Algorithms (243)

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 (10) Tweetations (7) Metrics

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  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