Machine learning algorithms for predicting the risk of fracture in patients with diabetes in China

BACKGROUND: Patients with diabetes are more likely to be predisposed to fractures compared to those without diabetes. In clinical practice, predicting fracture risk in diabetics is still difficult because of the limited availability and accessibility of existing fracture prediction tools in the diab...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Chu, Sijia, Jiang, Aijun, Chen, Lyuzhou, Zhang, Xi, Shen, Xiurong, Zhou, Wan, Ye, Shandong, Chen, Chao, Zhang, Shilu, Zhang, Li, Chen, Yang, Miao, Ya, Wang, Wei
Format: Online Artikel Text
Sprache:English
Veröffentlicht: Elsevier 2023
Schlagworte:
Research Article
Online Zugang:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10368844/
https://www.ncbi.nlm.nih.gov/pubmed/37501989
http://dx.doi.org/10.1016/j.heliyon.2023.e18186

Online

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10368844/
https://www.ncbi.nlm.nih.gov/pubmed/37501989
http://dx.doi.org/10.1016/j.heliyon.2023.e18186

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