Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis

Randomized controlled trials estimate average treatment effects, but treatment response heterogeneit...

RealSynCol: a high-fidelity synthetic colon dataset for 3D reconstruction applications

Deep learning has the potential to improve colonoscopy by enabling 3D reconstruction of the colon, p...

Reliable Mislabel Detection for Video Capsule Endoscopy Data

The classification performance of deep neural networks relies strongly on access to large, accuratel...

Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis

Liver tumour ablation presents a significant clinical challenge: whilst tumours are clearly visible ...

Fast Organ-of-Origin Classification for Digital Pathology Quality Control

Digitizing large histopathology archives requires processing millions of scanned whole slide images ...

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture

Early detection of colorectal cancer hinges on real-time, accurate polyp identification and resectio...

XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas

Accurate risk stratification of precancerous polyps during routine colonoscopy screenings is essenti...

Prediction of Mutations and Outcome in Gastrointestinal Stromal Tumors with Deep Learning: A Multicenter, Multinational Study

Background: Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tu...

Machine Learning Guided Optimization of an Oral Microemulsion System: A Bayesian Optimization Approach

Oral microemulsions are one drug delivery system often implemented to improve intestinal permeabilit...

AI quantification of inflammatory and architectural features in ulcerative colitis distinguishes active disease from remission

Background and Aims: Artificial intelligence (AI) is increasingly applied to histological assessment...

EndoCaver: Handling Fog, Blur and Glare in Endoscopic Images via Joint Deblurring-Segmentation

Endoscopic image analysis is vital for colorectal cancer screening, yet real-world conditions often ...

MoE-ACT: Improving Surgical Imitation Learning Policies through Supervised Mixture-of-Experts

Imitation learning has achieved remarkable success in robotic manipulation, yet its application to s...

Early and Prediagnostic Detection of Pancreatic Cancer from Computed Tomography

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest solid malignancies, is often detected ...

Developing a multi-domain EHR foundation model for predicting Hepatitis B liver disease: a clinical perspective

Foundation models trained on patient electronic health records (EHRs) hold promise for transforming ...

Learning with Geometric Priors in U-Net Variants for Polyp Segmentation

Accurate and robust polyp segmentation is essential for early colorectal cancer detection and for co...

Predicting Gene Mutations in Colon Cancer Using Long-Term Temporal Dependency Learning on a Directed Co-Occurrence Asymmetry Graph

Accurate prediction of mutational dependencies to model tumor evolution can improve our understandin...

Curated endoscopic retrograde cholangiopancreatography images dataset

Endoscopic Retrograde Cholangiopancreatography (ERCP) is a key procedure in the diagnosis and treatm...

Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation

Deep learning has substantially advanced medical image segmentation, yet achieving robust generaliza...

Transfer Learning from One Cancer to Another via Deep Learning Domain Adaptation

Supervised deep learning models often achieve excellent performance within their training distributi...

Using Multi-Instance Learning to Identify Unique Polyps in Colon Capsule Endoscopy Images

Identifying unique polyps in colon capsule endoscopy (CCE) images is a critical yet challenging task...

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