Gastroenterology

Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.

Type 2 diabetes is a polygenic, heterogeneous disease affecting over 530 million individuals worldwi...

Global trends in artificial intelligence applications for gastric cancer prediction, treatment, and management: a topic modeling and bibliometric analysis.

PURPOSE: Artificial intelligence (AI) emerged as a promising tool for enhancing healthcare delivery ...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells,...

Integrating multiphase MRI surrogates to improve microvascular invasion detection and recurrence risk stratification in HCC.

BACKGROUND & AIMS: Microvascular invasion (MVI) is a key determinant of recurrence and poor outcomes...

Lipidomic machine learning predictor for progression of gastric cancer.

BACKGROUND: Gastric cancer (GC) is a leading cause of global cancer mortality, characterized by aggr...

M3Hep: a multimodal hepatotoxicity prediction model combining mitochondrial toxicity and masking strategy.

Drug hepatotoxicity is one of the primary reasons for drug clinical trial failures and market withdr...

Bridging tradition and innovation: Acupuncture for depression through clinical efficacy and neurobiological insights.

BACKGROUND: To elucidate the research progress on acupuncture therapy as a complementary and alterna...

GICAF-Net: A cross-attentional graph-image fusion network for hyperspectral pathological diagnosis of FNH and HCC.

BACKGROUND AND OBJECTIVE: Accurate intraoperative differentiation between focal nodular hyperplasia ...

Feasibility of deep learning-accelerated HASTE-FS for pancreatic cystic lesion surveillance: comparison with conventional HASTE and MRCP.

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopa...

Abdominal multi-organ segmentation on 3D negative-contrast CT cholangiopancreatography: a comparative study of deep learning methods.

OBJECTIVES: This study aims to automate segmentation of the biliary and pancreatic systems on 3D neg...

Unsupervised machine learning for identifying morphological phenotypes in abdominal aortic aneurysms using fully automated volume-segmented imaging: a multicentre cohort study.

AIMS: Thrombo- and microembolic complications following abdominal aortic aneurysm (AAA) repair are h...

Deep-Learning Virtual Superior Mesenteric Artery Modeling for Risk Stratification in Pancreas Surgery.

BACKGROUND: Understanding the patient-specific anatomy of the superior mesenteric artery (SMA) and i...

White Light, Magnifying Endoscopy, Endocytoscopy, and Artificial Intelligence in Diagnosis of Early Colorectal Cancer: A Comparative Study.

OBJECTIVES: Early detection of colorectal cancer is critical for improving prognosis. However, asses...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Observation and Localization in CT Images.

Pancreatic cancer remains one of the deadliest malignancies, primarily because of its subtle CT appe...

Colonoscopy Quality and Strategies for Improvement.

Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and ...

Artificial intelligence in colon cancer: A commentary on advances and challenges.

Artificial intelligence-driven CT radiomics model predicts prognosis in TACE-refractory hepatocellular carcinoma.

PURPOSE: To develop an integrated predictive model combining radiomics, clinical risk factors, and m...

A CT-based 2.5D deep learning model for preoperative T-staging in gastric cancer: a retrospective multicenter study.

PURPOSE: To develop and validate a 2.5D multi-angle deep learning (MADL) model for preoperative T-st...

Intelligent ensemble learning-enhanced finite element modeling for precision thermal ablation in cancer therapy.

BACKGROUND: Microwave ablation (MWA) is a minimally invasive treatment for liver tumors, yet accurat...

Translating Gut Microbiota into Diagnostics: A Multidimensional Approach for the Diagnosis of Inflammatory Bowel Disease.

The gut microbiota has emerged as a key factor in the pathophysiology of inflammatory bowel disease ...

BiGraph-DTA: Predicting drug-target interactions of hepatoprotective agents with graph convolutional networks.

Predicting drug-target affinity (DTA) is critical for discovering and developing hepatoprotective ag...