The inaccurate predictions by Google Flu Trends in multiple seasons raised awareness of potential biases inherent in digital surveillance (65), including changes to search algorithms (stability), non-independence of data sources (posting and searching can be influenced by others), confounding (of search terms), ...
Nov 16, 2017 · Title:Deceptiveness of internet data for disease surveillance. Authors:Reid Priedhorsky, Dave Osthus, Ashlynn R. Daughton, Kelly R. Moran ...
Jul 31, 2018 · Our second metric, deceptiveness, addresses the issue that an estimate can be accurate for the wrong reasons. A deceptive search query is ...
Deceptiveness of internet data for disease surveillance · R. Priedhorsky, D. Osthus, +2 authors. A. Culotta · Published in arXiv.org 16 November 2017 · Computer ...
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... internet-based surveillance can complement traditional surveillance. 2. We introduce a new metric called deceptiveness that quantifies the risk of surveillance ...
We tested flu estimation models that incorporate information about this risk of deception, finding that knowledge of deceptiveness does indeed produce more ...
Bibliographic details on Deceptiveness of internet data for disease surveillance.
Sep 7, 2024 · We found that deceptiveness knowledge does reduce error in such estimates, that it may help automatically-selected features perform as well or ...
We found that deceptiveness knowledge does reduce error in such estimates, that it may help automatically- selected features perform as well or better than ...
Dec 5, 2022 · The application of internet search data has been seen as a novel data source to offer timely infectious disease surveillance intelligence.
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