Convolutional neural networks in the computer-aided diagnosis of Helicobacter pylori infection and non-causal comparison to physician endoscopists: a systematic review with meta-analysis.

ABSTRACT:

Background

Helicobacter pylori (H. pylori) infection, if left untreated, can cause gastric cancer, among other serious morbidities. In recent times, a growing body of evidence has evaluated the use of a type of artificial intelligence (AI) known as "deep learning" in the computer-aided diagnosis of H. pylori using convolutional neural networks (CNN). We conducted this meta-analysis to evaluate the pooled rates of performance of CNN-based AI in the diagnosis of H. pylori infection.

Methods

Multiple databases were searched (from inception to June 2020) and studies that reported on the performance of CNN in the diagnosis of H. pylori infection were selected. A random-effects model was used to calculate the pooled rates. In cases where multiple

SUBMITTER: Mohan BP 

PROVIDER: S-EPMC7774656 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature