Application of machine learning methods for the prediction of true fasting status in patients performing blood tests

The fasting blood glucose (FBG) values extracted from electronic medical records (EMR) are assumed valid in existing research, which may cause diagnostic bias due to misclassification of fasting status. We proposed a machine learning (ML) algorithm to predict the fasting status of blood samples. Thi...

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Detalles Bibliográficos
Autores principales: Chang, Shih-Ni, Hsiao, Ya-Luan, Lin, Che-Chen, Sun, Chuan-Hu, Chen, Pei-Shan, Wu, Min-Yen, Chen, Sheng-Hsuan, Chiang, Hsiu-Yin, Hsiao, Chiung-Tzu, King, Emily K., Chang, Chun-Min, Kuo, Chin-Chi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279373/
https://www.ncbi.nlm.nih.gov/pubmed/35831336
http://dx.doi.org/10.1038/s41598-022-15161-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279373/
https://www.ncbi.nlm.nih.gov/pubmed/35831336
http://dx.doi.org/10.1038/s41598-022-15161-2

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