Cargando…
An integrated machine learning predictive scheme for longitudinal laboratory data to evaluate the factors determining renal function changes in patients with different chronic kidney disease stages
BACKGROUND AND OBJECTIVES: Chronic kidney disease (CKD) is a global health concern. This study aims to identify key factors associated with renal function changes using the proposed machine learning and important variable selection (ML&IVS) scheme on longitudinal laboratory data. The goal is to...
Autores principales: | Tsai, Ming-Hsien, Jhou, Mao-Jhen, Liu, Tzu-Chi, Fang, Yu-Wei, Lu, Chi-Jie |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582636/ https://www.ncbi.nlm.nih.gov/pubmed/37859858 http://dx.doi.org/10.3389/fmed.2023.1155426 |
Ejemplares similares
-
A Hybrid Risk Factor Evaluation Scheme for Metabolic Syndrome and Stage 3 Chronic Kidney Disease Based on Multiple Machine Learning Techniques
por: Jhou, Mao-Jhen, et al.
Publicado: (2022) -
Important Risk Factors in Patients with Nonvalvular Atrial Fibrillation Taking Dabigatran Using Integrated Machine Learning Scheme—A Post Hoc Analysis
por: Huang, Yung-Chuan, et al.
Publicado: (2022) -
Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol
por: Liao, Pen-Chih, et al.
Publicado: (2022) -
Health Data-Driven Machine Learning Algorithms Applied to Risk Indicators Assessment for Chronic Kidney Disease
por: Chiu, Yen-Ling, et al.
Publicado: (2021) -
Evaluating the Effect of Topical Atropine Use for Myopia Control on Intraocular Pressure by Using Machine Learning
por: Wu, Tzu-En, et al.
Publicado: (2020)