Identifying patient characteristics that influence the rate of colorectal polyp recurrence can provide important insights into which patients are at higher risk for recurrence.
no code implementations • 27 Sep 2019 • Jason W. Wei, Arief A. Suriawinata, Louis J. Vaickus, Bing Ren, Xiaoying Liu, Mikhail Lisovsky, Naofumi Tomita, Behnaz Abdollahi, Adam S. Kim, Dale C. Snover, John A. Baron, Elizabeth L. Barry, Saeed Hassanpour
An accurate and automated algorithm for the classification of colorectal polyps on digitized histopathology slides could benefit clinicians and patients.
In this study, we trained a deep learning model to detect celiac disease on duodenal biopsy images.
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.