Gastroenterology

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 in inflammatory bowel disease (IBD), but most approaches quantify features in isolation and ignore their anatomical location within the mucosa. We developed and validated PAIR-IBD (Perspectum AI Reading in IBD), an AI system that quantifies inflammatory cell populations, crypt injury, and epithelia...

Predicting Rectal Cancer Patient Survival with Dutch Radiology Reports using Natural Language Processing (NLP): The Role of Pretrained Language Models

The use of Electronic Health Records (EHRs) has increased significantly in recent years. However, a substantial portion of the clinical data remains in unstructured text formats, especially in the context of radiology. This limits the application of EHRs for automated analysis in oncology research. Pretrained language models have been utilized to extract feature embeddings from these reports for d...

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 suffer from lens fogging, motion blur, and specula...

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 surgical robotics remains challenging due to data s...

Early and Prediagnostic Detection of Pancreatic Cancer from Computed Tomography

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest solid malignancies, is often detected at a late and inoperable stage. Retrospective revi...

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 clinical care by enabling effective decision suppo...

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 computer-aided diagnosis. While convolutional neural...

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 understanding of cancer progression and is crucial for early d...

Curated endoscopic retrograde cholangiopancreatography images dataset

Endoscopic Retrograde Cholangiopancreatography (ERCP) is a key procedure in the diagnosis and treatment of biliary and pancreatic diseases. Artificial...

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

Deep learning has substantially advanced medical image segmentation, yet achieving robust generalization across diverse imaging modalities and anatomi...

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

Supervised deep learning models often achieve excellent performance within their training distribution but struggle to generalize beyond it. In cancer...

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 for medical personnel due to the large volume of ...

Using deep learning for predicting cleansing quality of colon capsule endoscopy images

In this study, we explore the application of deep learning techniques for predicting cleansing quality in colon capsule endoscopy (CCE) images. Using ...

Pharmacogenomic Determinants of Post-Liver Transplant Diabetes Mellitus: A Systematic Review and In Silico Pharmacogenomic Analysis

Introduction: Tacrolimus remains central to liver transplantation, yet its narrow therapeutic index and pharmacokinetic variability are associated wit...

Refining cardiometabolic risk assessment using MRI-derived pancreas volume and fat content: insights from the NAKO and UK Biobank

BackgroundThe pancreas is essential for metabolic homeostasis. Alterations in morphology and parenchymal integrity may impact proper function but are ...

Achieving Expert-Level Clinical Infection Detection with LLMs from Clinical Documents: Validation in Complex Patient Cases with Cirrhosis

BackgroundSystemic infections are a leading cause of hospitalization and death among patients with cirrhosis. Timely and accurate infection identifica...

Onco-Seg: Adapting Promptable Concept Segmentation for Multi-Modal Medical Imaging

Medical image segmentation remains a critical bottleneck in clinical workflows, from diagnostic radiology to radiation oncology treatment planning. We...

Pairing-free Group-level Knowledge Distillation for Robust Gastrointestinal Lesion Classification in White-Light Endoscopy

White-Light Imaging (WLI) is the standard for endoscopic cancer screening, but Narrow-Band Imaging (NBI) offers superior diagnostic details. A key cha...

Development of potent humanized TNFα inhibitory nanobodies for therapeutic applications in TNFα-mediated diseases.

Tumor necrosis factor-alpha (TNFα) is a key pro-inflammatory cytokine implicated in the pathogenesis of numerous inflammatory and autoimmune diseases,...

Deep learning-based detection of bacterial swarm motion using a single image.

Motility is a fundamental characteristic of bacteria. Distinguishing between swarming and swimming, the two principal forms of bacterial movement, hol...