ArticleScientific reports2021
Infectious disease outbreak prediction using media articles with machine learning models.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
17 citing papers in PubMed.
- Acute respiratory infection (COVID-19) risk prediction in travelers: A random forest model.Infectious Disease Modelling · 2026Article
- Integrating explainable AI and One Health: a new frontier in combating infectious diseases.EBioMedicine · 2026Article
- An evaluation of a Bayesian method to track outbreaks of known and novel influenza-like illnesses.Scientific reports · 2026Article
- Machine Learning and Artificial Intelligence for Infectious Disease Surveillance, Diagnosis, and Prognosis.Viruses · 2025Review
- Global infectious disease early warning models: An updated review and lessons from the COVID-19 pandemic.Infectious Disease Modelling · 2025Review
- Pathways to strengthening the epidemic intelligence workforce.BMC proceedings · 2025Article
- Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.Frontiers in immunology · 2025Article
- An Integrated Framework for Infectious Disease Control Using Mathematical Modeling and Deep Learning.IEEE open journal of engineering in medicine and biology · 2025Article
- Article
- Forecasting the trend of tuberculosis incidence in Anhui Province based on machine learning optimization algorithm, 2013-2023.BMC pulmonary medicine · 2024Article
- Machine learning approaches to identify systemic lupus erythematosus in anti-nuclear antibody-positive patients using genomic data and electronic health records.BioData mining · 2024Article
- A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria.Frontiers in antibiotics · 2024Article
- Emerging infectious disease surveillance using a hierarchical diagnosis model and the Knox algorithm.Scientific reports · 2023Article
- Translating Predictive Analytics for Public Health Practice: A Case Study of Overdose Prevention in Rhode Island.American journal of epidemiology · 2023Article
- The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke.Journal of neuroengineering and rehabilitation · 2023Article
- Comparing and linking machine learning and semi-mechanistic models for the predictability of endemic measles dynamics.PLoS computational biology · 2022Article
- Development and application of survey-based artificial intelligence for clinical decision support in managing infectious diseases: A pilot study on a hospital in central Vietnam.Frontiers in public health · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
When a newly emerging infectious disease breaks out in a country, it brings critical damage to both human health conditions and the national economy. For this reason, apprehending which disease will newly emerge, and preparing countermeasures for that disease, are required. Many different types of infectious diseases are emerging and threatening global human health conditions. For this reason, the detection of emerging infectious disease pattern is critical. However, as the epidemic spread of infectious disease occurs sporadically and rapidly, it is not easy to predict whether an infectious disease will emerge or not. Furthermore, accumulating data related to a specific infectious disease is not easy. For these reasons, finding useful data and building a prediction model with these data is required. The Internet press releases numerous articles every day that rapidly reflect currently pending issues. Thus, in this research, we accumulated Internet articles from Medisys that were related to infectious disease, to see if news data could be used to predict infectious disease outbreak. Articles related to infectious disease from January to December 2019 were collected. In this study, we evaluated if newly emerging infectious diseases could be detected using the news article data. Support Vector Machine (SVM), Semi-supervised Learning (SSL), and Deep Neural Network (DNN) were used for prediction to examine the use of information embedded in the web articles: and to detect the pattern of emerging infectious disease.
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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.