Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers.

ABSTRACT:

Purpose

A growing number of studies have examined whether Artificial Intelligence (AI) systems can support imaging-based diagnosis of COVID-19-caused pneumonia, including both gains in diagnostic performance and speed. However, what is currently missing is a combined appreciation of studies comparing human readers and AI.

Methods

We followed PRISMA-DTA guidelines for our systematic review, searching EMBASE, PUBMED and Scopus databases. To gain insights into the potential value of AI methods, we focused on studies comparing the performance of human readers versus AI models or versus AI-supported human readings.

Results

Our search identified 1270 studies, of which 12 fulfilled specific selection criteria. Concerning diagnostic performance, in testing datasets reported s

SUBMITTER: Kriza C 

PROVIDER: S-EPMC8594127 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature