Machine Learning Models for Image-Based Diagnosis and Prognosis of COVID-19: Systematic Review.

ABSTRACT:

Background

Accurate and timely diagnosis and effective prognosis of the disease is important to provide the best possible care for patients with COVID-19 and reduce the burden on the health care system. Machine learning methods can play a vital role in the diagnosis of COVID-19 by processing chest x-ray images.

Objective

The aim of this study is to summarize information on the use of intelligent models for the diagnosis and prognosis of COVID-19 to help with early and timely diagnosis, minimize prolonged diagnosis, and improve overall health care.

Methods

A systematic search of databases, including PubMed, Web of Science, IEEE, ProQuest, Scopus, bioRxiv, and medRxiv, was performed for COVID-19-related studies published up to May 24, 2020. This study was performed in a

SUBMITTER: Montazeri M 

PROVIDER: S-EPMC8074953 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature