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Diabetic Retinopathy (DR) is one of the most common microvascular complications presenting by patients diagnosticated with diabetic diseases. Uncontrolled hyperglycemia may manifest as visual impairment and blindness. The early detection of DR is essential to minimize the risk and consequence of visual diminishing. The standard gold diagnoses tool relies on different imaging modalities and requires a judgment of expert photographers, which are not available in most of the primary care centers or remote location. In that scenario, an automate or semiautomated DR screening systems can contribute to improving the accuracy of the diagnostic. Thus, we performed a Systematic Review and Meta-Analysis to evaluate the Decision Support Systems (DSS) in diagnosing DR. The overall Diagnostic Odds Ratio was 73.15 (95%CI: 37.54-142.50), sensitivity was 97.70 (95%CI: 97.50-97.90) and specificity was 90.30 (95%CI: 90.00-90.60). Our results corroborate with the concept of usefulness of DSSs in early diagnosis, screening and preliminary evaluation of suspicious images of DR.

The aim of this study was to evaluate the accuracy of decision support systems in the diagnosis of breast cancer by means of a systematic review and meta-analysis of studies of diagnostic accuracy. The first step of the research, which consisted of the initial research of abstracts and titles identified from the research strategy in the databases was performed by two researchers independently. In this stage, 622 references were retrieved in the databases and, through a consensus meeting, 183 articles were selected for full reading.