Machine learning based biomarker discovery for chronic kidney disease-mineral and bone disorder (CKD-MBD).

ABSTRACT:

Introduction

Chronic kidney disease-mineral and bone disorder (CKD-MBD) is characterized by bone abnormalities, vascular calcification, and some other complications. Although there are diagnostic criteria for CKD-MBD, in situations when conducting target feature examining are unavailable, there is a need to investigate and discover alternative biochemical criteria that are easy to obtain. Moreover, studying the correlations between the newly discovered biomarkers and the existing ones may provide insights into the underlying molecular mechanisms of CKD-MBD.

Methods

We collected a cohort of 116 individuals, consisting of three subtypes of CKD-MBD: calcium abnormality, phosphorus abnormality, and PTH abnormality. To identify the best biomarker panel for discrimination, we cond

SUBMITTER: Li Y 

PROVIDER: S-EPMC10840173 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature