A Composite Retinal Fundus and OCT Dataset along with Detailed Clinical Markings for Extracting Retinal Layers, Retinal Lesions and Screening Macular and Glaucomatous Disorders

This dataset was designed to support research in AI-based medical image analysis, particularly focusing on retinal and pulmonary conditions. It includes thousands of expertly labeled OCT and Chest X-Ray images sourced from independent patients and categorized into four classes: CNV, DME, DRUSEN, and NORMAL. The dataset mirrors the imaging data described in the publication 'Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning', and is structured to facilitate reproducibility and benchmarking in deep learning workflows.

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