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

Natural Language Processing (692) Surveillance Systems (462) Secondary Use of Clinical Data for Research and Surveillance (366) Infectious Diseases (non-STD/STI) (1575)

Published on in Vol 6, No 2 (2018): Apr-Jun

Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore

Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore

Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore

Authors of this article:

Antony Hardjojo1 Author Orcid Image ;   Arunan Gunachandran1 Author Orcid Image ;   Long Pang1 Author Orcid Image ;   Mohammed Ridzwan Bin Abdullah1 Author Orcid Image ;   Win Wah1 Author Orcid Image ;   Joash Wen Chen Chong1 Author Orcid Image ;   Ee Hui Goh1 Author Orcid Image ;   Sok Huang Teo2 Author Orcid Image ;   Gilbert Lim3 Author Orcid Image ;   Mong Li Lee3 Author Orcid Image ;   Wynne Hsu3 Author Orcid Image ;   Vernon Lee1 Author Orcid Image ;   Mark I-Cheng Chen1, 4 Author Orcid Image ;   Franco Wong2, 5 Author Orcid Image ;   Jonathan Siung King Phang2, 5 Author Orcid Image
Article Authors Cited by (8) Tweetations (10) Metrics

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  2. Ganesan S, Galer P, Helbig K, McKeown S, O’Brien M, Gonzalez A, Felmeister A, Khankhanian P, Ellis C, Helbig I. A longitudinal footprint of genetic epilepsies using automated electronic medical record interpretation. Genetics in Medicine 2020;22(12):2060 View
  3. Woo K, Adams V, Wilson P, Fu L, Cato K, Rossetti S, McDonald M, Shang J, Topaz M. Identifying Urinary Tract Infection-Related Information in Home Care Nursing Notes. Journal of the American Medical Directors Association 2021;22(5):1015 View
  4. Naseri H, Kafi K, Skamene S, Tolba M, Faye M, Ramia P, Khriguian J, Kildea J. Development of a generalizable natural language processing pipeline to extract physician-reported pain from clinical reports: Generated using publicly-available datasets and tested on institutional clinical reports for cancer patients with bone metastases. Journal of Biomedical Informatics 2021;120:103864 View
  5. McKenzie J, Rajapakshe R, Shen H, Rajapakshe S, Lin A. A Semiautomated Chart Review for Assessing the Development of Radiation Pneumonitis Using Natural Language Processing: Diagnostic Accuracy and Feasibility Study. JMIR Medical Informatics 2021;9(11):e29241 View
  6. de Burgos‐Gonzalez A, Bryant V, Maciá‐Martinez M, Huerta C. A strategy for assessment and validation of major bleeding cases in a primary health care database in Spain. Pharmacoepidemiology and Drug Safety 2021;30(12):1696 View
  7. Van Olmen J, Van Nooten J, Philips H, Sollie A, Daelemans W. Predicting COVID-19 Symptoms From Free Text in Medical Records Using Artificial Intelligence: Feasibility Study. JMIR Medical Informatics 2022;10(4):e37771 View
  8. Omar M, Brin D, Glicksberg B, Klang E. Utilizing natural language processing and large language models in the diagnosis and prediction of infectious diseases: A systematic review. American Journal of Infection Control 2024;52(9):992 View