ArticleScientific reports2023
Using Bayesian networks with Tabu-search algorithm to explore risk factors for hyperhomocysteinemia.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Path and Bayesian network analyses in the complex design of a well-being survey via New Zealand's Integrated Data Infrastructure.Frontiers in psychiatry · 2026Article
- Article
- Risk factors and prediction model for acute ischemic stroke after off-pump coronary artery bypass grafting based on Bayesian network.BMC medical informatics and decision making · 2024Article
- Development of a chemiluminescent immunoassay based on magnetic solid phase for quantification of homocysteine in human serum.BMC biotechnology · 2024Article
- Development and validation of a routine blood parameters-based model for screening the occurrence of retinal detachment in high myopia in the context of PPPM.The EPMA journal · 2023Article
- Exploring factors related to heart attack complicated with hypertension using a Bayesian network model: a study based on the China Health and Retirement Longitudinal Study.Frontiers in public health · 2023Article
- Enhancing stroke-associated pneumonia prediction in ischemic stroke: An interpretable Bayesian network approach.Digital healthArticle
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hyperhomocysteinemia (HHcy) is a condition closely associated with cardiovascular and cerebrovascular diseases. Detecting its risk factors and taking some relevant interventions still represent the top priority to lower its prevalence. Yet, in discussing risk factors, Logistic regression model is usually adopted but accompanied by some defects. In this study, a Tabu Search-based BNs was first constructed for HHcy and its risk factors, and the conditional probability between nodes was calculated using Maximum Likelihood Estimation. Besides, we tried to compare its performance with Hill Climbing-based BNs and Logistic regression model in risk factor detection and discuss its prospect in clinical practice. Our study found that Age, sex, α1-microgloblobumin to creatinine ratio, fasting plasma glucose, diet and systolic blood pressure represent direct risk factors for HHcy, and smoking, glycosylated hemoglobin and BMI constitute indirect risk factors for HHcy. Besides, the performance of Tabu Search-based BNs is better than Hill Climbing-based BNs. Accordingly, BNs with Tabu Search algorithm could be a supplement for Logistic regression, allowing for exploring the complex network relationship and the overall linkage between HHcy and its risk factors. Besides, Bayesian reasoning allows for risk prediction of HHcy, which is more reasonable in clinical practice and thus should be promoted.
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