Artificial intelligence model on chest imaging to diagnose COVID-19 and other pneumonias: A systematic review and meta-analysis.

ABSTRACT:

Objectives

When diagnosing Coronavirus disease 2019(COVID-19), radiologists cannot make an accurate judgments because the image characteristics of COVID-19 and other pneumonia are similar. As machine learning advances, artificial intelligence(AI) models show promise in diagnosing COVID-19 and other pneumonias. We performed a systematic review and meta-analysis to assess the diagnostic accuracy and methodological quality of the models.

Methods

We searched PubMed, Cochrane Library, Web of Science, and Embase, preprints from medRxiv and bioRxiv to locate studies published before December 2021, with no language restrictions. And a quality assessment (QUADAS-2), Radiomics Quality Score (RQS) tools and CLAIM checklist were used to assess the quality of each study. We used random-e

SUBMITTER: Jia LL 

PROVIDER: S-EPMC9385733 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature