AIMC Topic: Population Health
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Supervised mixture of experts models for population health.
Methods (San Diego, Calif.)
May 21, 2020
We propose a machine learning driven approach to derive insights from observational healthcare data to improve public health outcomes. Our goal is to simultaneously identify patient subpopulations with differing health risks and to find those risk fa...
The AI Revolution and How to Prepare for It.
Translational vision science & technology
Mar 18, 2020
A population health perspective on artificial intelligence.
Healthcare management forum
May 19, 2019
The burgeoning field of Artificial Intelligence (AI) has the potential to profoundly impact the public's health. Yet, to make the most of this opportunity, decision-makers must understand AI concepts. In this article, we describe approaches and field...
Defining ethical standards for the application of digital tools to population health research.
Bulletin of the World Health Organization
Jan 17, 2019
There is growing interest in population health research, which uses methods based on artificial intelligence. Such research draws on a range of clinical and non-clinical data to make predictions about health risks, such as identifying epidemics and m...
Machine learning in population health: Opportunities and threats.
PLoS medicine
Nov 27, 2018
Abraham D. Flaxman and Theo Vos of the Institute for Health Metrics and Evaluation, University of Washington, discuss near-term applications for ML in population health and name their priorities for ongoing ML development.
Artificial intelligence to improve cardiovascular population health.
European heart journal
May 21, 2025
With the advent of artificial intelligence (AI), novel opportunities arise to revolutionize healthcare delivery and improve population health. This review provides a state-of-the-art overview of recent advancements in AI technologies and their applic...
[Digital environment and population health].
Revue medicale suisse
Apr 17, 2024
Health and risk of disease are determined by exposure to the physical, socio-economic, and political environment and to this has been added exposure to the digital environment. Our increasingly digital lives have major implications for people's healt...
Predicting Avoidable Health Care Utilization: Practical Considerations for Artificial Intelligence/Machine Learning Models in Population Health.
Mayo Clinic proceedings
Apr 1, 2022
Creative Approaches for Assessing Long-term Outcomes in Children.
Pediatrics
Jul 1, 2021
Advances in new technologies, when incorporated into routine health screening, have tremendous promise to benefit children. The number of health screening tests, many of which have been developed with machine learning or genomics, has exploded. To as...
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