Gastroenterology

Pancreatic Diseases

Latest AI and machine learning research in pancreatic diseases for healthcare professionals.

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Comparative Evaluation of Machine Learning and Deep Learning Models for Early Prediction of Severe Acute Pancreatitis: A Multi-Model Study Using the 2012 Revised Atlanta Classification

**Background:** Acute pancreatitis (AP) is a common gastrointestinal emergency with a subset of patients progressing to severe acute pancreatitis (SAP), which carries substantial morbidity and mortality. Current clinical severity scores such as BISAP, APACHE II, Ranson, and the Modified CT Severity Index require upon 48 hours of observation before reliable assessment is possible, limiting early tr...

Body composition subphenotypes, cardiometabolic risk and incident outcomes: validation in the population-based NAKO and UK Biobank imaging cohorts

Background Anthropometric measures do not adequately capture heterogeneity in body fat distribution and corresponding cardiometabolic risk, whereas magnetic resonance imaging (MRI) enables precise differentiation and quantification of adipose tissue compartments and ectopic fat. We aimed to validate previously derived MRI-based body composition subphenotypes and their cardiometabolic risk profiles...

Enhancing Road Safety: An IoT-Based Accident Detection and Prevention Mechanism

Road traffic accidents remain a critical global crisis, consistently serving as a primary driver of preventable mortality and severe injury. These inc...

Jun 21 2026 2606.22381v1
SegDINO: Introducing Multi-Scale Structure into DINO for Efficient Medical Image Segmentation

Self-supervised DINO models provide strong transferable visual representations, yet applying them directly to image segmentation remains challenging. ...

Jun 16 2026 2606.17972v1
Conversational Artificial Intelligence-Enabled Precision Oncology Reveals Context-Specific TGFβ and JAK/STAT Alterations in Pancreatic Cancer

Background: Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive molecular complexity, profound stromal remodeling, and limited respo...

Transcriptomic Architecture of Type 2 Diabetes in Human Pancreatic Islets:An Integrative Meta-Analysis and Machine Learning Framework for Biomarker Discovery

Background. Type 2 diabetes mellitus (T2D) is defined by progressive pancreatic {beta}-cell dysfunction whose molecular underpinnings remain incomplet...

AI-guided analysis of human pancreatic islet sociology reveals distinct cell compositional changes in type 1 diabetes

Human pancreatic islets exhibit greater anatomic and cellular heterogeneity than previously appreciated, raising fundamental questions about how their...

A Comparison of Manual and Automated Approaches to Developing Computable Algorithms for Identifying Acute Pancreatitis

Objective: Clinical phenotyping methods that rely on clinical and informatics expertise can be time-intensive and costly. We tested both manual and hi...

CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space

Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, morphological feature ex...

Multi-Algorithm Machine Learning Benchmarking for Pan-Cancer Classification from Tumour-Educated Platelet RNA Sequencing

Tumour-educated platelets (TEPs) carry cancer-type-specific RNA signatures accessible through whole-blood RNA sequencing, but systematic multi-algorit...

SCKAN: Structural Consensus-based KAN Prototype Learning for Semi-Supervised Pancreas Segmentation

Accurate pancreas segmentation is critical for early cancer diagnosis, where annotation scarcity necessitates Semi-Supervised Learning (SSL). However,...

May 26 2026 2605.27032v1
Overweight status drives early tumor microenvironment reprogramming in pancreatic ductal adenocarcinoma: a cell-type-resolved Bayesian hierarchical modeling and interactome analysis

Background: Obesity significantly increases the risk of prognosis and clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). While research on ...

DynoSys 2.0: Graph-Based Modeling of Dynamic Risk States and System Transitions in Human Behaviours Development

Human behavioral and mental health outcomes arise from interactions among genetic, environmental, and neurobiological systems. Existing frameworks oft...

InterScale reveals multi-scale cellular interaction programs in spatial transcriptomics

Tissue homeostasis and disease emerge from cell-cell interactions operating across spatial scales: from autocrine and juxtacrine signals within microm...

Interpreting Omics Data Analysis with Large Language Models for Disease Target and Drug Discovery

In biomedical scientific discovery, synthesizing prior knowledge from the literature is an essential component of interpreting numerical omics data an...

Dual GLP-1/FGF21 agonism suppresses voluntary alcohol consumption, alcohol choice, and nucleus accumbens dopamine modulation

Excessive alcohol consumption remains a major public health challenge with limited therapeutic options. Both glucagon-like peptide-1 (GLP-1) and fibro...

Prediction of Alzheimer's Disease Risk Factors from Retinal Images via Deep Learning: Development and Validation of Biologically Relevant Morphological Associations in the UK Biobank

The systemic, metabolic, lifestyle factors have established associations with Alzheimer's Disease (AD) through epidemiologic and AD-specific biomarker...

May 1 2026 2605.00665v1
Disease Risk Prediction Using Structured EHR Data: Can Generalist Large Language Models Match Specialized Clinical Foundation Models? A Comparative Evaluation with Fine-Tuning

Background: Electronic health records (EHRs) with clinical decision support tools are now ubiquitous in healthcare organizations. Clinical foundation ...

DIANNE: Segmentation-Free Localization of Histology Differential Attributes

Pathologist-guided distinctions within histology and spatial omic images provide insights into health and disease, with digital pathology leveraging a...

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