ArticlemedRxiv : the preprint server for health sciences2025
An evaluation of a Bayesian method to track outbreaks of known and novel influenza-like illnesses.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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6 authors.
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Abstract
Tracking known influenza-like illnesses, such as influenza, is an important problem in public health and clinical medicine. The problem is complicated by the clinical similarity and co-occurrence of many of these illnesses. Additionally, detecting a new or reemergent disease, such as COVID-19, is of paramount importance as recent history has shown. This paper describes the testing of a system that tracks known influenza-like illnesses and can detect the presence of a novel disease.
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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.