Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand

Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand

Abstract Background In the age of big data, linked social and administrative health data in combination with machine learning (ML) is being increasingly used to improve prediction in chronic disease, e.g., cardiovascular diseases (CVD). In this study we aimed to apply ML methods on extensive nationa...

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Bibliographic Details
Main Authors: Nhung Nghiem, Nick Wilson, Jeremy Krebs, Truyen Tran
Format: Article
Language:English
Published: BMC 2024-09-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Machine learning
Diabetes complications
Cardiovascular disease
Risk prediction
Health and social administrative data
Online Access:https://doi.org/10.1186/s12911-024-02678-x

Internet

https://doi.org/10.1186/s12911-024-02678-x

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