Peptic Ulcer Disease

MEF-Net: Multi-scale and edge feature fusion network for intracranial hemorrhage segmentation in CT images.

Intracranial Hemorrhage (ICH) refers to cerebral bleeding resulting from ruptured blood vessels within the brain. Delayed and inaccurate diagnosis and treatment of ICH can lead to fatality or disability. Therefore, early and precise diagnosis of intracranial hemorrhage is crucial for protecting patients' lives. Automatic segmentation of hematomas in CT images can provide doctors with essential dia...

Integrative PPI network and random forest analysis identifies KIF4A, TOP2A, and ASPM protein macromolecules as novel protein biomarkers in renal carcinoma pathogenesis.

The pathogenesis of kidney cancer is not fully understood, so there is an urgent need to identify new biomarkers to improve diagnosis and treatment. The study identified KIF4A, TOP2A and ASPM as novel protein biomarkers for renal cancer and explored their biological functions in the development and progression of renal cancer. A variety of bioinformatics methods were used to process and batch cali...

Federated Foundation Model for GI Endoscopy Images

Gastrointestinal (GI) endoscopy is essential in identifying GI tract abnormalities in order to detect diseases in their early stages and improve pat...

Federated Foundation Model for GI Endoscopy Images

Gastrointestinal (GI) endoscopy is essential in identifying GI tract abnormalities in order to detect diseases in their early stages and improve pat...

Automated diagnosis for extraction difficulty of maxillary and mandibular third molars and post-extraction complications using deep learning.

Optimal surgical methods require accurate prediction of extraction difficulty and complications. Although various automated methods related to third m...

A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis

Endoscopic procedures are essential for diagnosing and treating internal diseases, and multi-modal large language models (MLLMs) are increasingly ap...

Statistical Inference under Performativity

Performativity of predictions refers to the phenomena that prediction-informed decisions may influence the target they aim to predict, which is wide...

DanceTogether! Identity-Preserving Multi-Person Interactive Video Generation

Controllable video generation (CVG) has advanced rapidly, yet current systems falter when more than one actor must move, interact, and exchange posi...

Anatomy-Guided Multitask Learning for MRI-Based Classification of Placenta Accreta Spectrum and its Subtypes

Placenta Accreta Spectrum Disorders (PAS) pose significant risks during pregnancy, frequently leading to postpartum hemorrhage during cesarean deliv...

Point, Detect, Count: Multi-Task Medical Image Understanding with Instruction-Tuned Vision-Language Models

We investigate fine-tuning Vision-Language Models (VLMs) for multi-task medical image understanding, focusing on detection, localization, and counti...

SAMA-UNet: Enhancing Medical Image Segmentation with Self-Adaptive Mamba-Like Attention and Causal-Resonance Learning

Medical image segmentation plays an important role in various clinical applications, but existing models often struggle with the computational ineff...

EndoVLA: Dual-Phase Vision-Language-Action Model for Autonomous Tracking in Endoscopy

In endoscopic procedures, autonomous tracking of abnormal regions and following circumferential cutting markers can significantly reduce the cogniti...

Characterization of subepithelial tumors of upper gastrointestinal tract by endoscopic ultrasound.

In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment outcome of esophageal gastrointestinal stromal tu...

Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial.

BACKGROUND: Invasive coronary angiography (ICA) is the gold standard in the diagnosis of coronary artery disease (CAD). Being invasive, it carries rar...

PRS-Med: Position Reasoning Segmentation with Vision-Language Model in Medical Imaging

Recent advancements in prompt-based medical image segmentation have enabled clinicians to identify tumors using simple input like bounding boxes or ...

VitaGraph: Building a Knowledge Graph for Biologically Relevant Learning Tasks

The intrinsic complexity of human biology presents ongoing challenges to scientific understanding. Researchers collaborate across disciplines to exp...

Informed, but Not Always Improved: Challenging the Benefit of Background Knowledge in GNNs

In complex and low-data domains such as biomedical research, incorporating background knowledge (BK) graphs, such as protein-protein interaction (PP...

Advances in gastrointestinal endoscopy: A comprehensive review of innovations in cancer diagnosis and management.

The field of gastroenterology has experienced revolutionary advances over the past years, as flexible endoscopes have become widely accessible. In add...

GNN-Suite: a Graph Neural Network Benchmarking Framework for Biomedical Informatics

We present GNN-Suite, a robust modular framework for constructing and benchmarking Graph Neural Network (GNN) architectures in computational biology...

Multi-contrast laser endoscopy for in vivo gastrointestinal imaging

White light endoscopy is the clinical gold standard for detecting diseases in the gastrointestinal tract. Most applications involve identifying visu...