Article

Interpretable Machine Learning based Detection of Coeliac Disease

2025-03-11

Abstract excerpt

<h4>Background</h4> Coeliac disease, an autoimmune disorder affecting approximately 1% of the global population, is typically diagnosed on duodenal biopsy. However, inter-pathologist agreement on coeliac disease diagnosis is only 80%. Existing machine learning solutions designed to improve coeliac disease diagnosis often lack interpretability, which is essential for building trust and enabling widespread clinical...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 2cfef8b9-28fc-5ae2-be1c-2e9d42a3a729
DOI: 10.1101/2025.03.11.25323763

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Interpretable Machine Learning based Detection of Coeliac DiseaseDOI 10.1101/2025.03.11.25323763Read

Celiac Disease Image Classification using Convolutional Neural NetworkSemantic proximity Read

Screening of normal endoscopic large bowel biopsies with artificial intelligence: a retrospective studySemantic proximity Read

Closing the Paediatric Gap: Adult-Trained AI Generalises Robustly to Paediatric Coeliac Disease DiagnosisSemantic proximity Read

Prediction of Celiac Disease Severity and Associated Endocrine Morbidities through Deep Learning-based Image AnalyticsSemantic proximity Read

Using Deep Learning to Automate Eosinophil Counting in Pediatric Ulcerative Colitis Histopathological ImagesSemantic proximity Read

Robust and accurate diagnosis of infectious skin diseases from histopathology images by integrating deep learning and explainable AISemantic proximity Read

AI based pre-screening of large bowel cancer via weakly supervised learning of colorectal biopsy histology imagesSemantic proximity Read

A Clinical Benchmark of Foundation Models: Towards Reliable Morphological Subtyping and Cancer Detection on Real-World Barrett’s Esophagus DataSemantic proximity Read

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal PathologySemantic proximity Read

Automating Ground Truth Annotations For Gland Segmentation Through ImmunohistochemistrySemantic proximity Read

Accurate Diagnosis of Colorectal Cancer Based on Histopathology Images Using Artificial IntelligenceSemantic proximity Read

Integrating etiological insights with machine learning for precision diagnosis of obstructive jaundice: Findings from a high-volume centerSemantic proximity Read