期刊
PLOS ONE
卷 17, 期 7, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0271331
关键词
-
资金
- Generalitat Valenciana through IVACE (Valencian Institute of Business Competitiveness) [IMDEEA-2021-100]
Unplanned hospital readmissions are burdensome for health systems. This paper proposes a machine learning classification and risk stratification approach to estimate readmission risk and provide a decision support system based on patient risk scores.
Unplanned hospital readmissions mean a significant burden for health systems. Accurately estimating the patient's readmission risk could help to optimise the discharge decision-making process by smartly ordering patients based on a severity score, thus helping to improve the usage of clinical resources. A great number of heterogeneous factors can influence the readmission risk, which makes it highly difficult to be estimated by a human agent. However, this score could be achieved with the help of AI models, acting as aiding tools for decision support systems. In this paper, we propose a machine learning classification and risk stratification approach to assess the readmission problem and provide a decision support system based on estimated patient risk scores.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据