PhD
Assistant Professor of Medical Informatics
Department of Health Information Management,
School of Allied Medical Sciences
Shahid Beheshti University of Medical Sciences
Tehran, Iran
PhD
Assistant Professor of Health Information Management
Department of Medical Library and Information Sciences,
School of Allied Medical Sciences
Shahid Beheshti University of Medical Sciences
Tehran, Iran
Professor of Cardiac Anesthesia;
Editor in Chief,
JCMA
Anesthesiology Research Center
Shahid Beheshti University of Medical Sciences,
Tehran, Iran
Journal of Cellular & Molecular Anesthesia:
Vol.5, issue 1; e149607
published online:
April
09,
2020
article type:
Original Articles
How To Cite
Rahmatizadeh
S, Valizadeh-Haghi
S, Dabbagh
A. The role of Artificial Intelligence in Management of Critical COVID-19 patients. J Cell Mol Anesth. 2020;5(1):e149607. https://doi.org/10.22037/jcma.v5i1.29752.
Abstract
Background: the COVID-19 outbreak has created a great challenge for the healthcare system worldwide. One of the most critical points of this challenge is the management of COVID-19 patients needing acute and/or critical respiratory care. This study was performed to discover an AI based model to improve the critical care of the COVID-19 patients.Material and methods: in a descriptive study, all the published research available in PubMed, Web of Science, Google scholar and other databases were retrieved. Based on these studies, a three stage model of input, process and output was created.Results: the three stage model of AI application in ICU was completed. Input included Clinical, Paraclinical, Personalized Medicine (OMICS) and Epidemiologic data. The process included Artificial Intelligence (i.e. Artificial Neural Network, Machine Learning, Deep Learning and Expert Systems). The output which was ICU Decision Making included Diagnosis, Treatment, Risk Stratification, Prognosis and Management.Conclusion: the efforts of the healthcare system to defeat COVID-19 could be supported by an AI-based decision-making system which would double them up and help manage these patients much more efficiently, especially those in COVID-19 ICU
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