Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study

Opportunely screening for diabetes is crucial to reduce its related morbidity, mortality, and socioeconomic burden. Machine learning (ML) has excellent capability to maximize predictive accuracy. We aim to develop ML-augmented models for diabetes screening in community and primary care settings. 842...

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Vydané v:	Frontiers in endocrinology (Lausanne) Ročník 13; s. 1043919
Hlavní autori:	Liu, XiaoHuan, Zhang, Weiyue, Zhang, Qiao, Chen, Long, Zeng, TianShu, Zhang, JiaoYue, Min, Jie, Tian, ShengHua, Zhang, Hao, Huang, Hantao, Wang, Ping, Hu, Xiang, Chen, LuLu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 28.11.2022
Predmet:	Algorithms community and primary care diabetes Diabetes Mellitus - diagnosis Diabetes Mellitus - epidemiology Endocrinology health economic evaluation Humans Machine Learning Mass Screening ML-augmented algorithm Primary Health Care screening screening ML-augmented algorithm health economic evaluation diabetes community and primary care
ISSN:	1664-2392, 1664-2392
On-line prístup:	Získať plný text
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