Disease Prediction

An open-source Optical Coherence Tomography Image Database containing different retinal OCT images with various pathological conditions. This comprehensive open-access database contains over 500 high-resolution images categorized into different pathological conditions. The image classes include Normal (NO), Macular Hole (MH), Age-related Macular Degeneration (AMD), Central Serous Retinopathy (CSR), and Diabetic Retinopathy (DR).

The goal of the challenge is to compare automated algorithms that are able to detect and segment various types of fluids on a common dataset of optical coherence tomography (OCT) volumes representing different retinal diseases, acquired with devices from different manufacturers. We made available a dataset of OCT volumes containing a wide variety of retinal fluid lesions with accompanying reference annotations. We invite the medical imaging community to participate by developing and testing existing and novel automated retinal OCT segmentation methods.

PreRAID is a structured dataset designed to evaluate the diagnostic capabilities of Large Language Models (LLMs) in Rheumatoid Arthritis (RA) diagnosis. This dataset provides real-world patient data, offering insights into RA prediction and reasoning accuracy.