Shahabedin Rahmatizadeh - Department of Health Information Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Saeideh Valizadeh-Haghi - Department of Medical Library and Information Sciences, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Ali Dabbagh - Department of Anesthesiology, School of Medicine, Anesthesiology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Coronavirus disease ۲۰۱۹ (COVID-۱۹) 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-۱۹ 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-۱۹ patients. 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. Three stages model of AI application in intensive care unit (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. Efforts of the healthcare system to defeat COVID-۱۹ 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-۱۹ ICU.

Artificial intelligence, COVID-۱۹, Critical care