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

Abstract 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-communic...

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Main Authors: Sharon Birdi, Roxana Rabet, Steve Durant, Atushi Patel, Tina Vosoughi, Mahek Shergill, Christy Costanian, Carolyn P. Ziegler, Shehzad Ali, David Buckeridge, Marzyeh Ghassemi, Jennifer Gibson, Ava John-Baptiste, Jillian Macklin, Melissa McCradden, Kwame McKenzie, Sharmistha Mishra, Parisa Naraei, Akwasi Owusu-Bempah, Laura Rosella, James Shaw, Ross Upshur, Andrew D. Pinto
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Public Health
Subjects:
Population health
Non-communicable disease
Machine learning
Artificial intelligence
Online Access:https://doi.org/10.1186/s12889-024-21081-9
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https://doi.org/10.1186/s12889-024-21081-9

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