<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Eosinophilic Esophagitis E-113_B</dcterms:title><dcterms:identifier>https://doi.org/10.18130/V3/RYVJRD</dcterms:identifier><dcterms:creator>Sengupta, Saurav</dcterms:creator><dcterms:publisher>University of Virginia Dataverse</dcterms:publisher><dcterms:issued>2024-11-12</dcterms:issued><dcterms:modified>2024-11-12T16:36:14Z</dcterms:modified><dcterms:description>Eosinophilic esophagitis (EoE) is an inflammatory disease diagnosed by ≥15 intraepithelial eosinophils (Eos) in an esophageal biopsy high-power field. This is a Whole Slide Image (WSI) containing eosinophils that we use to train an AI model to automatically detect and count these cellular structures in a given image to reduce the data annotation burden on clinicians and pathologists.</dcterms:description><dcterms:subject>Other</dcterms:subject><dcterms:subject>imaging</dcterms:subject><dcterms:subject>eoe</dcterms:subject><dcterms:subject>eosinophilic gastrointestinal disease</dcterms:subject><dcterms:subject>healthcare deep learning</dcterms:subject><dcterms:subject>gut intelligenceai</dcterms:subject><dcterms:date>2024-11-12</dcterms:date><dcterms:contributor>Sengupta, Saurav</dcterms:contributor><dcterms:dateSubmitted>2024-11-12</dcterms:dateSubmitted><dcterms:license>CC0 1.0</dcterms:license></metadata>