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.
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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