Health AI Central
Share:
Peer-Reviewed Publication
BMJ Open Gastroenterol2025;12(1)December 7, 2025Journal Article

Comparative evaluation of a hybrid machine learning-human adjudication paradigm for endoscopic scoring in ulcerative colitis.

Klaus T Gottlieb1, Chakib Battioui2, Yeli Wang3, Pavel A Brodskiy3, Mohammad Haft-Javaherian3, Daniel R Colucci3, Darren Thomason3, Shrujal Baxi3
1Eli Lilly and Company, Indianapolis, Indiana, USA klaus.gottlieb@gmail.com.
2Eli Lilly and Company, Indianapolis, Indiana, USA.
3Iterative Health Inc, Cambridge, Massachusetts, USA.
PubMed PMC DOI PDF

Abstract

OBJECTIVE: Endoscopic scoring of disease activity is essential in ulcerative colitis trials but is limited by inter-reader variability and operational complexity. We evaluated a novel central reading paradigm integrating two independently developed machine learning models with human adjudication for discordant cases ('2M+1H') to determine whether it is statistically non-inferior to the traditional…

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.