Latest AI and machine learning research in gastroenterology for healthcare professionals.
OBJECTIVES: Early detection and resection of colorectal polyps prevent their progression toward advanced adenocarcinomas. The use of Texture and Color Enhancement Imaging (TXI) has been demonstrated to enhance adenoma detection compared to white light imaging. It remains unknown whether there is an additive benefit when using computer-aided detection (CADe) in addition to enhanced imaging technolo...
BACKGROUND: The clinical comorbidity of diabetes mellitus (DM) and gastric cancer (GC) presents a significant healthcare challenge, as these two conditions often synergistically promote disease progression. Although Epimedium is known for its anti-tumor and metabolic regulatory properties, the precise molecular mechanism by which it intervenes in the DM-GC comorbidity remains poorly understood. ME...
INTRODUCTION: Exposure to ionizing radiation by endoscopy personnel during fluoroscopy-guided procedures remains a health hazard. We aimed to evaluate...
Accurate soleus (SOL) activation assessment is essential for Achilles tendon rupture (ATR) recovery, yet direct measurement remains a clinical challen...
BACKGROUND: Disulfidptosis is a novel form of glucose starvation-induced cell death, yet its prognostic implications in gastric cancer (GC) remain lar...
High-resolution spatial transcriptomics requires computational methods to accurately assign transcripts to individual cells. We present SMURF (Segment...
Due to its high genomic heterogeneity and dense desmoplastic microenvironment, traditional diagnosis and treatment for pancreatic ductal adenocarcinom...
The pancreas is local in the retroperitoneal space,in close proximity to critical blood vessels such as celiac trunk, superior mesenteric artery, hepa...
Postoperative pulmonary infection (PPI) after esophageal cancer surgery occurs frequently and severely impairs patients' prognosis. Most existing pred...
BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...
BACKGROUND AND AIMS: High-quality, annotated datasets are fundamental to clinical research and artificial intelligence (AI) model development. Existin...
Depression and non-alcoholic fatty liver disease (NAFLD) are increasingly recognized as interconnected disorders, yet the causal mechanisms linking th...
BACKGROUND: To develop and validate a deep learning (DL) model based on feature fusion with B-mode ultrasound (BMUS) and contrast enhanced ultrasound ...
This study aimed to develop a robust prediction model- using machine-learning algorithms based on the core indicators of the tumor immune microenviron...
BACKGROUND: Research on the early detection of pancreatic cancer has grown rapidly in recent years; however, existing bibliometric studies in this fie...
Traditional TNM staging inadequately captures the recurrence risk of rectal cancer (RC), limiting prognostic accuracy and personalized treatment decis...
OBJECTIVE: To develop and validate a machine learning (ML) algorithm for predicting 30-day mortality in adult patients with acute pancreatitis (AP) us...
OBJECTIVE: Comprehensive identification and prioritization of developed artificial intelligence methods for applications of radiology can help to sele...
BACKGROUND: Medical education relies on experience to develop clinical reasoning skills, yet patient access is often limited. Large language models (L...
BACKGROUND: Chronic liver disease (CLD) and its progression to compensated cirrhosis (CC), decompensated cirrhosis (DC), and acute-on-chronic liver fa...