Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models

Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models

Background: AI-driven digital health tools often rely on estimates of disease incidence or prevalence, but obtaining these estimates is costly and time-consuming. We explored the use of machine learning models that leverage contextual information about diseases from unstructured text, to estimate di...

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Bibliographic Details
Main Authors: Yuanzhao Zhang, Robert Walecki, Joanne R. Winter, Felix J. S. Bragman, Sara Lourenco, Christopher Hart, Adam Baker, Yura Perov, Saurabh Johri
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-12-01
Series:Frontiers in Digital Health
Subjects:
natural language processing
disease incidence
health statistic data
deep learning
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2020.569261/full

Internet

https://www.frontiersin.org/articles/10.3389/fdgth.2020.569261/full

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