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...

Full description

Saved in:

Bibliographic Details
Published in:	Frontiers in endocrinology (Lausanne) Vol. 13; p. 1043919
Main Authors:	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
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 28.11.2022
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!