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Predict Turnaround Time of Hospital Discharge
2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2022 ; : 408-414, 2022.
Article in English | Scopus | ID: covidwho-2323859
ABSTRACT
COVID-19 pandemics lead to further shortages of beds globally. Ningbo No.1 Hospital implemented an integrated digital management system to tackle inefficiency in the discharge process, however, this problem is not fully solved. To help the hospital fully address this problem, this article identifies the problems in the hospital's dataset and proposes a methodology for the machine learning model training in order to predict the patient's leaving time, which provides a space for the hospital to improve the discharge process when procedures simplify, integration and digitalization are done. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: WIC Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: WIC Year: 2022 Document Type: Article