ArticleJournal of the American Medical Informatics Association : JAMIA2019
Development of a global infectious disease activity database using natural language processing, machine learning, and human expertise.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Integrating mathematical modelling and artificial intelligence to combat emerging viral syndemics: A systematic review.New microbes and new infections · 2026Review
- Early Warning of Infectious Disease Outbreaks Using Social Media and Digital Data: A Scoping Review.International journal of environmental research and public health · 2025Article
- Development of an Integrated Surveillance System to Improve Preparedness for Arbovirus Outbreaks in a Dengue Endemic Setting: Descriptive Study.JMIR public health and surveillance · 2024Article
- Approaches for the Use of AI in Workplace Health Promotion and Prevention: Systematic Scoping Review.JMIR AI · 2024Article
- Opportunities and challenges of 5G network technology toward precision medicine.Clinical and translational science · 2023Review
- Dissemination of information in event-based surveillance, a case study of Avian Influenza.PloS one · 2023Article
- A Data-Driven Paradigm for a Resilient and Sustainable Integrated Health Information Systems for Health Care Applications.Journal of multidisciplinary healthcare · 2023Article
- Automated Classification of Online Sources for Infectious Disease Occurrences Using Machine-Learning-Based Natural Language Processing Approaches.International journal of environmental research and public health · 2020Article
- Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science.Yearbook of medical informatics · 2020Review
- Challenges and opportunities for public health made possible by advances in natural language processing.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2020Article
- Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic.NAM perspectives · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe assessed whether machine learning can be utilized to allow efficient extraction of infectious disease activity information from online media reports. MATERIALS AND
methodsWe curated a data set of labeled media reports (n = 8322) indicating which articles contain updates about disease activity. We trained a classifier on this data set. To validate our system, we used a held out test set and compared our articles to the World Health Organization Disease Outbreak News reports.
resultsOur classifier achieved a recall and precision of 88.8% and 86.1%, respectively. The overall surveillance system detected 94% of the outbreaks identified by the WHO covered by online media (89%) and did so 43.4 (IQR: 9.5-61) days earlier on average. DISCUSSION: We constructed a global real-time disease activity database surveilling 114 illnesses and syndromes. We must further assess our system for bias, representativeness, granularity, and accuracy.
conclusionMachine learning, natural language processing, and human expertise can be used to efficiently identify disease activity from digital media reports.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.