Risk prediction of hypertension complications based on the intelligent algorithm optimized Bayesian network

DOI10.1007/S10878-019-00485-ZzbMath1482.90229OpenAlexW2990833937MaRDI QIDQ2060069

Xiaoling Ouyang, Gang Du, Xi Liang, Chunming Wang

Publication date: 13 December 2021

Published in: Journal of Combinatorial Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10878-019-00485-z

zbMATH Keywords

risk predictionimproved particle swarm optimizationhypertension complicationsintelligent algorithm optimized Bayesian network

Mathematics Subject Classification ID

Programming involving graphs or networks (90C35) Applications of mathematical programming (90C90) Approximation methods and heuristics in mathematical programming (90C59)

Cites Work

• Unnamed Item
• Unnamed Item
• Quadratic kernel-free least squares support vector machine for target diseases classification
• How patient compliance impacts the recommendations for colorectal cancer screening
• A survey of cross-validation procedures for model selection
• Evidential reasoning using stochastic simulation of causal models
• A Bayesian method for the induction of probabilistic networks from data
• Bayesian network classifiers
• Study on specialist outpatient matching appointment and the balance matching model
• Real-time scheduling optimization considering the unexpected events in home health care
• Analysis of cough detection index based on decision tree and support vector machine

This page was built for publication: Risk prediction of hypertension complications based on the intelligent algorithm optimized Bayesian network