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

Natural Language Processing (869) Surveillance Systems (507) Secondary Use of Clinical Data for Research and Surveillance (453) Infectious Diseases (non-STD/STI) (1700)

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 (9) 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
  9. McMurry A, Phelan D, Dixon B, Geva A, Gottlieb D, Jones J, Terry M, Taylor D, Callaway H, Manoharan S, Miller T, Olson K, Mandl K. Large Language Model Symptom Identification From Clinical Text: Multicenter Study. Journal of Medical Internet Research 2025;27:e72984 View