Modeling methodology for early warning of chronic heart failure based on real medical big data
作者：
Highlights：
• Construct a medical social network to describe the similarity among risk factors.
• The personal health can be denoted as a probabilistic combination of risk factors.
• Propose a division algorithm to divide the network into a high and low risk group.
• Propose a heart failure risk prediction method, which accuracy can reach almost 90.
• Set four tests to measure the effectiveness of our method.
摘要
•Construct a medical social network to describe the similarity among risk factors.•The personal health can be denoted as a probabilistic combination of risk factors.•Propose a division algorithm to divide the network into a high and low risk group.•Propose a heart failure risk prediction method, which accuracy can reach almost 90.•Set four tests to measure the effectiveness of our method.
论文关键词：Heart failure,Early warning,Social network,Risk factors,Medical big data
论文评审过程：Received 4 August 2019, Revised 20 February 2020, Accepted 5 March 2020, Available online 6 March 2020, Version of Record 13 March 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113361
