Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection
10.1186/1472-6947-14-75
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| 其他作者: | |
| 格式: | Article |
| 出版: |
2020
|
| 主題: | |
| 在線閱讀: | https://scholarbank.nus.edu.sg/handle/10635/181489 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | National University of Singapore |
| id |
sg-nus-scholar.10635-181489 |
|---|---|
| record_format |
dspace |
| spelling |
sg-nus-scholar.10635-1814892024-11-11T23:28:09Z Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection Liu, N Koh, Z.X Goh, J Lin, Z Haaland, B Ting, B.P Ong, M.E.H DUKE-NUS MEDICAL SCHOOL aged artificial intelligence Chest Pain emergency health service female Heart Diseases heart rate human male middle aged physiology procedures prognosis statistical model Aged Artificial Intelligence Chest Pain Emergency Service, Hospital Female Heart Diseases Heart Rate Humans Male Middle Aged Models, Statistical Prognosis Triage 10.1186/1472-6947-14-75 BMC Medical Informatics and Decision Making 14 1 75 2020-10-27T11:05:33Z 2020-10-27T11:05:33Z 2014 Article Liu, N, Koh, Z.X, Goh, J, Lin, Z, Haaland, B, Ting, B.P, Ong, M.E.H (2014). Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection. BMC Medical Informatics and Decision Making 14 (1) : 75. ScholarBank@NUS Repository. https://doi.org/10.1186/1472-6947-14-75 14726947 https://scholarbank.nus.edu.sg/handle/10635/181489 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Unpaywall 20201031 |
| institution |
National University of Singapore |
| building |
NUS Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NUS Library |
| collection |
ScholarBank@NUS |
| topic |
aged artificial intelligence Chest Pain emergency health service female Heart Diseases heart rate human male middle aged physiology procedures prognosis statistical model Aged Artificial Intelligence Chest Pain Emergency Service, Hospital Female Heart Diseases Heart Rate Humans Male Middle Aged Models, Statistical Prognosis Triage |
| spellingShingle |
aged artificial intelligence Chest Pain emergency health service female Heart Diseases heart rate human male middle aged physiology procedures prognosis statistical model Aged Artificial Intelligence Chest Pain Emergency Service, Hospital Female Heart Diseases Heart Rate Humans Male Middle Aged Models, Statistical Prognosis Triage Liu, N Koh, Z.X Goh, J Lin, Z Haaland, B Ting, B.P Ong, M.E.H Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| description |
10.1186/1472-6947-14-75 |
| author2 |
DUKE-NUS MEDICAL SCHOOL |
| author_facet |
DUKE-NUS MEDICAL SCHOOL Liu, N Koh, Z.X Goh, J Lin, Z Haaland, B Ting, B.P Ong, M.E.H |
| format |
Article |
| author |
Liu, N Koh, Z.X Goh, J Lin, Z Haaland, B Ting, B.P Ong, M.E.H |
| author_sort |
Liu, N |
| title |
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| title_short |
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| title_full |
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| title_fullStr |
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| title_full_unstemmed |
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| title_sort |
prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection |
| publishDate |
2020 |
| url |
https://scholarbank.nus.edu.sg/handle/10635/181489 |
| _version_ |
1821196016865509376 |