Deep learning for detection of age-related macular degeneration: A systematic review and meta-analysis of diagnostic test accuracy studies.

ABSTRACT:

Objective

To evaluate the diagnostic accuracy of deep learning algorithms to identify age-related macular degeneration and to explore factors impacting the results for future model training.

Methods

Diagnostic accuracy studies published in PubMed, EMBASE, the Cochrane Library, and ClinicalTrails.gov before 11 August 2022 which employed deep learning for age-related macular degeneration detection were identified and extracted by two independent researchers. Sensitivity analysis, subgroup, and meta-regression were performed by Review Manager 5.4.1, Meta-disc 1.4, and Stata 16.0. The risk of bias was assessed using QUADAS-2. The review was registered (PROSPERO CRD42022352753).

Results

The pooled sensitivity and specificity in this meta-analysis were 94% (P = 0, 95% CI 0.

SUBMITTER: Leng X 

PROVIDER: S-EPMC10079062 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature