Gastroenterology

Indocyanine green fluorescence for intraoperative detection of liver tumours in minimally invasive surgery: protocol for the LIVERGREEN phase IV multicentre clinical trial.

INTRODUCTION: Liver tumours are a leading cause of global morbidity and mortality. Current diagnostic tools, including computed tomography (CT), magnetic resonance imaging (MRI) and intraoperative ultrasound (IOUS), have limitations in detecting liver neoplasms. Indocyanine green (ICG) has emerged as a promising tool for improving liver tumour detection. This study aims to assess the impact of pre...

Circulating extracellular vesicle long RNA profiling combined with machine learning unveils novel diagnostic signature and molecular features in chronic pancreatitis.

BACKGROUND: No clinically useful non-invasive biomarkers have been developed for diagnosis of chronic pancreatitis (CP), and molecular features of CP have not been characterised. Extracellular vesicles (EVs) consisted of abundant RNA species with specialised functions and clinical applications. OBJECTIVE: Our study aimed to construct a diagnostic model for CP and depict molecular landscape of CP b...

Automated deep learning for real-time focal liver lesions detection in ultrasound videos a multicenter study.

Early detection of focal liver lesions (FLLs) is crucial for clinical practice, but ultrasound performance heavily depends on operator experience. We ...

Inflammatory bowel disease burden in China and the United States from 1990-2023 and prediction to 2050.

BACKGROUND: Inflammatory bowel disease (IBD) shows divergent epidemiological trends in China and the United States, necessitating country-specific for...

Molecular Biomarkers and Risk Prediction Models for Acute Kidney Injury Following Liver Transplantation: A Review.

Liver transplantation is the definitive treatment for end-stage liver disease; however, postoperative acute kidney injury (AKI) affects 30%-70% of rec...

MRI-driven multimodal deep learning approach for predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: A multicenter study.

OBJECTIVES: Achieving a pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal c...

Magnetic resonance imaging-based radiomics of mesorectum for predicting extramural venous invasion in patients with rectal cancer: a bi-centric study.

OBJECTIVES: To develop and validate a magnetic resonance imaging (MRI)-based radiomics model of the mesorectum for predicting extramural venous invasi...

Machine learning-based multi-omic analysis identifies CEP55, DLGAP5, and EZH2 as regulated cell death biomarkers linked to immunotherapy resistance in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often exhibits limited responsiveness to immune checkpoint inhibitors (ICIs), largely due to an immunosuppressive tumor...

Early prediction of bowel necrosis in incarcerated groin hernia using parsimonious machine learning models: a retrospective cohort study.

A Preliminary Study of a Machine Learning Prediction of Poorly Differentiated Hepatocellular Carcinoma Based on a Comprehensive Parameter Analysis Using Dual-Energy Computed Tomography.

OBJECTIVE: To develop and evaluate the performance of a predictive machine learning model for poorly differentiated hepatocellular carcinoma (p-HCC) u...

HP-DIL: Deep heterogeneity profiling with graph-informed disentangled interaction learning for MRI-based liver fibrosis staging.

Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease. Multiparametric MRI enables non-invasive, quantit...

Deep Learning-Based Contrast-Enhanced Ultrasound for Ki-67 Assessment and Prognosis in Hepatocellular Carcinoma.

Ki-67 is a critical prognostic marker for hepatocellular carcinoma (HCC), yet its clinical assessment relies on invasive biopsy. This study aimed to d...

AI triage of duodenal biopsies improves workflow.

AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopatholog...

A deep learning-based digital biopsy for predicting early recurrence in gastric cancer.

Early postoperative recurrence is a major cause of treatment failure in patients with locally advanced gastric cancer (LAGC), yet current staging syst...

Imaging in the diagnosis and characterization of tennis leg.

Tennis leg is a common cause of acute posteromedial calf pain and encompasses a spectrum of injuries involving the posterior calf. Although initially ...

Convergence of multiplexed immunosensors, nanotechnology, and AI for early pancreatic cancer diagnosis.

Pancreatic cancer (PC) remains one of the deadliest malignancies, largely because of its asymptomatic onset, rapid progression, and absence of sensiti...

Identification and Validation of Transcriptomic Signatures in Inflammatory Bowel Disease with Metabolic Syndrome via Bioinformatics and Machine Learning.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic, nonspecific inflammatory disorder affecting the gastrointestinal tract. The condition's pat...

Identification of senescence-related genes as diagnostic biomarkers for gastric cancer using bioinformatics and machine learning.

Exploration of the roles of SSR2 in hepatocellular carcinogenesis based on single-cell transcriptomics and spatial transcriptomics.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of cancer globally. However, HCC features poor prognosis due to complex pat...

A deep learning-driven automated treatment planning framework for cervical cancer patients treated with volumetric modulated arc therapy.

BACKGROUND AND PURPOSE: The rapid and efficient generation of high-quality, dose-consistency volumetric modulated arc therapy (VMAT) plans remains cha...