使用机器学习方法研究血液因子与血液中HDL-C水平之间的关系。

IF 2.8 3区 医学 Q3 ENVIRONMENTAL SCIENCES
Somayeh Ghiasi Hafezi, Marzieh Hosseini, Mahtab Panahi, Sahar Arab Yousefabadi, Amin Mansoori, Iman Atighi, Mark Ghamsary, Gordon Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan
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引用次数: 0

摘要

本研究探讨了血脂成分与代谢紊乱,特别是对心血管健康至关重要的高密度脂蛋白胆固醇(HDL-C)之间的关系。它使用逻辑回归(LR)、决策树(DT)、随机森林(RF)、k近邻(KNN)、XGBoost (XGB)和神经网络(NN)算法来探索血液因素如何影响血液中HDL-C水平。方法:该研究涉及9704名参与者,分为正常和低HDL-C水平。使用数据挖掘方法(如LR、DT、RF、KNN、XGB和NN)分析数据以预测HDL-C测量。此外,DT用于确定HDL-C测量的预测模型。结果:本研究使用多种ML模型确定了HDL-C水平的性别特异性血液学预测因子。逻辑回归表现出最高的性能。NHR和LHR分别是男性和女性中最具影响力的预测因子,SHAP分析证实了它们与LYM、NEUT和WBC在HDL-C分类中的关键作用。讨论:结果表明,血液炎症在HDL-C稳态中起作用。这些关系的机制尚不完全清楚,但炎症与HDL-C水平以及心脏代谢健康之间的复杂相互作用是显而易见的。这些发现支持了炎症途径在心脏代谢紊乱中的病理生理作用,并为血液炎症的调节如何有助于疾病的预防或治疗提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating the relationship between blood factors and HDL-C levels in the bloodstream using machine learning methods.

Introduction: The study investigates the relationship between blood lipid components and metabolic disorders, specifically high-density lipoprotein cholesterol (HDL-C), which is crucial for cardiovascular health. It uses logistic regression (LR), decision tree (DT), random forest (RF), K-nearest neighbors (KNN), XGBoost (XGB), and neural networks (NN) algorithms to explore how blood factors affect HDL-C levels in the bloodstream.

Method: The study involved 9704 participants, categorized into normal and low HDL-C levels. Data was analyzed using a data mining approach such as LR, DT, RF, KNN, XGB, and NN to predict HDL-C measurement. Additionally, DT was used to identify the predictive model for HDL-C measurement.

Result: This study identified gender-specific hematological predictors of HDL-C levels using multiple ML models. Logistic regression exhibited the highest performance. NHR and LHR were the most influential predictors in males and females, respectively, with SHAP analysis confirming their critical roles alongside LYM, NEUT, and WBC in HDL-C classification.

Discussion: The results show that blood inflammation plays a role in HDL-C homeostasis. The mechanisms of these relationships are not fully understood, but a complex interplay between inflammation and HDL-C levels as well as cardiometabolic health is evident. These findings support the pathophysiological role of inflammatory pathways in cardiometabolic disorders and provide insights into how modulation of hematological inflammation may contribute to disease prevention or treatment.

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来源期刊
Journal of Health, Population, and Nutrition
Journal of Health, Population, and Nutrition 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.20
自引率
0.00%
发文量
49
审稿时长
6 months
期刊介绍: Journal of Health, Population and Nutrition brings together research on all aspects of issues related to population, nutrition and health. The journal publishes articles across a broad range of topics including global health, maternal and child health, nutrition, common illnesses and determinants of population health.
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