https://scholars.lib.ntu.edu.tw/handle/123456789/596555
標題: | A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study | 作者: | Yao, Li-Hung Leung, Ka-Chun CHU-LIN TSAI CHIEN-HUA HUANG LI-CHEN FU |
關鍵字: | data to text; deep learning; electronic health record; emergency department; hospital admission; triage system | 公開日期: | 2021 | 出版社: | JMIR PUBLICATIONS, INC | 卷: | 23 | 期: | 12 | 來源出版物: | Journal of Medical Internet Research | 摘要: | Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treatment, it still heavily relies on the nurse's subjective judgment and triages too many patients to emergency severity index level 3 in current practice. Hence, a system that can help clinicians accurately triage a patient's condition is imperative. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/596555 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121990464&doi=10.2196%2f27008&partnerID=40&md5=5c0ebd8387459f47f59b861c83415660 |
ISSN: | 1438-8871 | DOI: | 10.2196/27008 | SDG/關鍵字: | adult; article; clinical outcome; cohort analysis; controlled study; convolutional neural network; deep learning; electronic health record; electronic medical record; emergency health service; emergency ward; female; hospital admission; hospitalization; human; intensive care unit; major clinical study; male; medical care; mortality; outcome assessment; prediction; prospective study; receiver operating characteristic; recurrent neural network; resource allocation; retrospective study; Taiwan; university hospital; electronic health record; hospital emergency service; retrospective study; Deep Learning; Electronic Health Records; Emergency Service, Hospital; Hospitalization; Humans; Prospective Studies; Retrospective Studies; Triage |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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