Diagnostic performance of deep learning models in retinal vein occlusion: a systematic review and meta-analysis.

Diagnostic Performance of Deep Learning Using Retinal Images for Detection of Chronic Kidney Disease: A Systematic Review and Meta-analysis.

BACKGROUND Multiple investigations have been conducted to diagnose chronic kidney disease (CKD) from photographs of retina using deep learning models, with a wide range of diagnostic performance, which necessitates the importance of a comprehensive review. Therefore, in this meta-analysis, we estimated the detection pe...

Deep Learning Algorithms for the Diagnosis and Staging of Retinopathy of Prematurity: A Systematic Review and Meta-Analysis

The objective of this systematic review and meta-analysis is to evaluate artificial intelligence (AI) algorithms that diagnose and stage retinopathy of prematurity (ROP). Diagnostic accuracy studies reporting metrics of algorithms using fundus images for ROP identification and staging were included and evaluated. Meta-...

Diagnostic accuracy of AI-augmented renal ultrasound for degenerative kidney disorders: a systematic review and meta-analysis

Abstract Introduction This systematic review and meta-analysis evaluated artificial intelligence (AI) and radiomics applied to renal ultrasound for the diagnosis, staging, and prognosis of degenerative kidney disorders. Methods PubMed/MEDLINE, Embase, Scopus, Web of Science, the Cochrane Library, and gray-literature so...

Applications and performance of imaging artificial intelligence in detecting and staging avascular necrosis of the femoral head: a systematic review and meta-analysis.

Deep learning models for pancreatic cancer detection on CT: a meta-analysis

Findings suggest the potential of DL as a decision-support tool, but they should be interpreted with caution, and prospective multicenter validation studies are urgently needed before clinical integration can be recommended.

Artificial Intelligence for Real-Time Any-Stage Diabetic Retinopathy Detection: Systematic Review and Meta-analysis

Introduction: Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults worldwide. Traditional manual screening methods are often time-consuming and require specialized resources, limiting their accessibility. This review evaluates the diagnostic accuracy of artificial intelligence (AI)–assiste...