New study reveals disparities in the predictive performance of US-based type 2 diabetes risk scores between non-Hispanic Blacks and non-Hispanic Whites
#### Credit: The image was AI-created using DALL·E by OpenAI. Tibor V. Varga owns the image, including the right to reprint, sell, and merchandise (Usage Rights in https://labs.openai.com/about). The image is distributed under the CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) #### Article URL: https://journals.plos.org/climate/article?id=10.1371/journal.pgph.0001556 Article Title: Assessing racial bias in type 2 diabetes risk prediction algorithms Author […]
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Credit: The image was AI-created using DALL·E by OpenAI. Tibor V. Varga owns the image, including the right to reprint, sell, and merchandise (Usage Rights in https://labs.openai.com/about). The image is distributed under the CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/)
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Article URL: https://journals.plos.org/climate/article?id=10.1371/journal.pgph.0001556
Article Title: Assessing racial bias in type 2 diabetes risk prediction algorithms
Author Countries: Denmark
Funding: HTC and AK are supported by a grant from Novo Nordisk Foundation Challenge Programme for the project Harnessing the Power of Big Data to Address the Societal Challenge of Aging (NNF17OC0027812). TOA is supported by a grant from the Independent Research Fund Denmark (7025-00005B). TVV is supported by the “Data Science Investigator – Emerging 2022” grant from Novo Nordisk Foundation (NNF22OC0075284). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Journal
PLOS Global Public Health
DOI
10.1371/journal.pgph.0001556
Article Title
Assessing racial bias in type 2 diabetes risk prediction algorithms
Article Publication Date
17-May-2023
COI Statement
The authors have declared that no competing interests exist.
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