Healthcare Operations and Black Swan Event for COVID-19 Pandemic: A Predictive Analytics

COVID-19 pandemic has questioned the way healthcare operations take place globally as the healthcare professionals face an unprecedented task of controlling and treating the COVID-19 infected patients with a highly straining and draining facility due to the erratic admissions of infected patients. H...

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Bibliographic Details
Published in:	IEEE transactions on engineering management Vol. 70; no. 9; pp. 3229 - 3243
Main Authors:	Devarajan, Jinil Persis, Manimuthu, Arunmozhi, Sreedharan, V Raja
Format:	Journal Article
Language:	English
Published:	United States IEEE 01-09-2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Black swan event Corona COVID-19 COVID-19 (novel corona) Cycle ratio Cycle time data analytics Data models Decision making deep learning Drainage facilities Emerging Technologies Engineering Management extreme learning machine (ELM) Health care long short-term memory (LSTM) Machine learning Mathematical analysis Medical personnel Medical services multilayer perceptron Pandemics prediction Predictions Predictive analytics Predictive models Project Management Resource management Technology Assessment, Forecasting, Planning and Transfer time series Time series analysis deep learning data analytics long short-term memory (LSTM) multilayer perceptron prediction time series COVID-19 (novel corona) extreme learning machine (ELM)
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