Background: Type 2 diabetes (T2D) is one of the most prevalent chronic diseases worldwide and a leading cause of cardiorenal disease and mortality. Only one-third of individuals with T2D receive care as recommended by the American Diabetes Association's clinical practice guidelines. Effective strategies are needed to accelerate the implementation of guideline concordant T2D care.
View Article and Find Full Text PDFImportance: Deep learning image analysis often depends on large, labeled datasets, which are difficult to obtain for rare diseases.
Objective: To develop a self-supervised approach for automated classification of macular telangiectasia type 2 (MacTel) on optical coherence tomography (OCT) with limited labeled data.
Design, Setting, And Participants: This was a retrospective comparative study.
Background: Emergency departments (EDs) are the primary source of health care for many patients diagnosed with sexually transmitted infections (STIs). Expedited partner therapy (EPT), treating the partner of patients with STIs, is an evidence-based practice for patients who might not otherwise seek care. Little is known about the use of EPT in the ED.
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