Health AI Central
Share:
Peer-Reviewed Publication
Gastro Hep Adv2023;2(7):935-942.January 1, 2023Journal Article

Development of a Novel Ulcerative Colitis Endoscopic Mayo Score Prediction Model Using Machine Learning.

David T Rubin1, Klaus Gottlieb2, Jean-Frederic Colombel3, Jean-Pierre Schott4,5, Lavi Erisson4,6, Bill Prucka7, Sloane Allebes Phillips4, John Kwon8, Jonathan Ng4, James McGill2
1University of Chicago Medicine Inflammatory Bowel Disease Center, Gastroenterology, Chicago, Illinois.
2Eli Lilly and Company, Immunology, Indianapolis, Indiana.
3Icahn School of Medicine at Mount Sinai, Gastroenterology, New York, New York.
4Iterative Scopes, Inc., Cambridge, Massachusetts.
5KelaHealth, Inc., San Francisco, California.
6Gensaic, Inc., Cambridge, Massachusetts.
7Eli Lilly and Company, Advanced Analytics and Data Sciences, Indianapolis, Indiana.
8Janssen Pharmaceuticals, Immunology, Raritan, New Jersey.
PubMed PMC DOI PDF

Abstract

BACKGROUND AND AIMS: Endoscopic assessment is a co-primary end point in inflammatory bowel disease registration trials, yet it is subject to inter- and intraobserver variability. We present an original machine learning approach to Endoscopic Mayo Score (eMS) prediction in ulcerative colitis and report the model's performance in differentiating key levels of endoscopic disease activity on full-leng…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.