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Found 4 papers, 1 papers with code
Predicting colorectal polyp recurrence using time-to-event analysis of medical records
Identifying patient characteristics that influence the rate of colorectal polyp recurrence can provide important insights into which patients are at higher risk for recurrence.
Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation
An accurate and automated algorithm for the classification of colorectal polyps on digitized histopathology slides could benefit clinicians and patients.
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
It achieved a kappa score of 0. 525 and an agreement of 66. 6% with three pathologists for classifying the predominant patterns, slightly higher than the inter-pathologist kappa score of 0. 485 and agreement of 62. 7% on this test set.
Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach
In this study, we trained a deep learning model to detect celiac disease on duodenal biopsy images.
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