Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression

Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression

Abstract High-sensitivity C-reactive protein (hs-CRP) is a biomarker of inflammation predicting the incidence of different health pathologies. In this study, we aimed to evaluate the association between hematological and demographic factors with hs-CRP levels using decision tree (DT) and linear regr...

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Main Authors: Somayeh Ghiasi Hafezi, Toktam Sahranavard, Alireza Kooshki, Marzieh Hosseini, Amin Mansoori, Elham Amir Fakhrian, Helia Rezaeifard, Mark Ghamsary, Habibollah Esmaily, Majid Ghayour-Mobarhan
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
High sensitivity C-reactive protein
Hematological factors
Demographic parameters
Decision tree
Online Access:https://doi.org/10.1038/s41598-024-81714-2
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https://doi.org/10.1038/s41598-024-81714-2

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