Accuracy of artificial intelligence model for infectious keratitis classification: a systematic review and meta-analysis.

ABSTRACT:

Background

Infectious keratitis (IK) is a sight-threatening condition requiring immediate definite treatment. The need for prompt treatment heavily depends on timely diagnosis. The diagnosis of IK, however, is challenged by the drawbacks of the current "gold standard." The poorly differentiated clinical features, the possibility of low microbial culture yield, and the duration for culture are the culprits of delayed IK treatment. Deep learning (DL) is a recent artificial intelligence (AI) advancement that has been demonstrated to be highly promising in making automated diagnosis in IK with high accuracy. However, its exact accuracy is not yet elucidated. This article is the first systematic review and meta-analysis that aims to assess the accuracy of available DL models to correctl

SUBMITTER: Sarayar R 

PROVIDER: S-EPMC10704127 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature