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

Presentations, Abstracts, or Demonstrations (740) Machine Learning (1501) Influenza and Influenza-Like-Illness (ILI) Surveillance (219)

Published on in Vol 5, No 1 (2013):

Detection of Patients with Influenza Syndrome Using Machine-Learning Models Learned from Emergency Department Reports

Detection of Patients with Influenza Syndrome Using Machine-Learning Models Learned from Emergency Department Reports

Detection of Patients with Influenza Syndrome Using Machine-Learning Models Learned from Emergency Department Reports

Authors of this article:

Arturo Lopez Pineda1 ;   Fu-Chiang Tsui1 ;   Shyam Visweswaran1 ;   Gregory F. Cooper1
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Journals

  1. Dolatabadi E, Chen B, Buchan S, Austin A, Azimaee M, McGeer A, Mubareka S, Kwong J. Natural Language Processing for Clinical Laboratory Data Repository Systems: Implementation and Evaluation for Respiratory Viruses. JMIR AI 2023;2:e44835 View
  2. Ferraro J, Ye Y, Gesteland P, Haug P, Tsui F, Cooper G, Bree R, Ginter T, Nowalk A, Wagner M. The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance. Applied Clinical Informatics 2017;08(02):560 View