Name
Title | ||
|---|---|---|
Discover high-risk factor combinations using Bayesian network from cohort data of National Stoke Screening in China. |
Abstract | ||
|---|---|---|
We find that the criteria used in preliminary screening are not reasonable enough. There is a need for national stroke screening and intervention program to further include some more important risk factors or combinations of two risk factors as classification criteria in the preliminary screening. The results of the study can directly guide stroke screening program in China to make the screening more accurate and efficient. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1186/s12911-019-0753-8 | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Bayesian network,High-risk factors,National Stroke Screening | Population,Causality,China,Knowledge management,Stroke,Bayesian network,Environmental health,Health informatics,Cohort,Medicine,Risk factor | Journal |
Volume | Issue | ISSN |
19-S | 2 | 1472-6947 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuemeng Li | 1 | 0 | 2.37 |
| Jianfei Pang | 2 | 0 | 3.04 |
| Mei Li | 3 | 2 | 11.53 |
| Dongsheng Zhao | 4 | 0 | 1.35 |