https://scholars.lib.ntu.edu.tw/handle/123456789/535580
標題: | Prediction of ROSC After Cardiac Arrest Using Machine Learning | 作者: | Liu, Nan Ho, Andrew Fu Wah Pek, Pin Pin TSUNG-CHIEN LU Khruekarnchana, Pairoj Song, Kyoung Jun Tanaka, Hideharu Naroo, Ghulam Yasin Gan, Han Nee Koh, Zhi Xiong MATTHEW HUEI-MING MA Ong, Marcus |
關鍵字: | Out-of-hospital cardiac arrest; ROSC; machine learning; random forest | 公開日期: | 16-六月-2020 | 卷: | 270 | 來源出版物: | Studies in health technology and informatics | 摘要: | Out-of-hospital cardiac arrest (OHCA) is an important public health problem, with very low survival rate. In treating OHCA patients, the return of spontaneous circulation (ROSC) represents the success of early resuscitation efforts. In this study, we developed a machine learning model to predict ROSC and compared it with the ROSC after cardiac arrest (RACA) score. Results demonstrated the usefulness of machine learning in deriving predictive models. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/535580 | DOI: | 10.3233/SHTI200440 | SDG/關鍵字: | Machine learning; Medical informatics; Medicine; Resuscitation; Cardiac arrest; Machine learning models; Predictive models; Survival rate; Predictive analytics; emergency health service; human; machine learning; out of hospital cardiac arrest; physiological process; resuscitation; retrospective study; survival rate; Cardiopulmonary Resuscitation; Emergency Medical Services; Humans; Machine Learning; Out-of-Hospital Cardiac Arrest; Physiological Phenomena; Retrospective Studies; Survival Rate |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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