Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review

Background Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable dise...

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Bibliographic Details
Main Authors: Birdi, Sharon, Rabet, Roxana, Durant, Steve, Patel, Atushi, Vosoughi, Tina, Shergill, Mahek, Costanian, Christy, Ziegler, Carolyn P., Ali, Shehzad, Buckeridge, David, Ghassemi, Marzyeh, Gibson, Jennifer, John-Baptiste, Ava, Macklin, Jillian, McCradden, Melissa, McKenzie, Kwame
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: BioMed Central 2025
Online Access:https://hdl.handle.net/1721.1/157937

Internet

https://hdl.handle.net/1721.1/157937

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