Gastroenterology

Non-invasive diagnosis of metabolic dysfunction-associated steatotic liver disease: Current status, challenges, and future directions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent liver disease...

Cross-modality fusion of hematology-based digital and molecular biomarkers for intelligent epidemiological screening and surveillance of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains a critical challenge due to the disease's ...

Curriculum for safe and effective use of artificial intelligence in endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement.

The European Society of Gastrointestinal Endoscopy (ESGE) has identified a critical need to establis...

Machine Learning-Augmented Graphene Transistor Biosensing: Quantitative Platform Validation and Immunotesting of Hepatitis E.

Graphene-based chips face persistent sensor-to-sensor variability due to manufacturing defects and p...

Discovery of hemostatic component combination from Nelumbinis Receptaculum using dual machine learning spectrum-effect analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Nelumbinis Receptaculum (NR) were hemostatic herbal medicines for tr...

Addressing Colonoscopy Burden Due to Artificial Intelligence Devices for Polyp Detection.

Skill degradation, false-positive burden, and translational gap of artificial intelligence-assisted colonoscopy.

Automated Segmentation of Liver and Liver Tumors with SwinUNETR and UNET Neural Networks on 18F-FDG PET/CT.

OBJECTIVES: To develop and evaluate automated segmentation models for the liver and hepatic tumors o...

Integrating lesser omentum adipose CT in dual-phase tumor imaging: A multi-label deep learning framework for preoperative microvascular invasion prediction and survival analysis in hepatocellular carcinoma.

BACKGROUND AND OBJECTIVE: Accurate preoperative prediction of microvascular invasion (MVI) and survi...

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease.

OBJECTIVES: Exclusive enteral nutrition (EEN) is a first-line treatment for induction of remission i...

Acetyl tributyl citrate induces intestinal toxicity by regulating the IDH2/NF-κB pathway and lipid peroxidation.

In recent years, the increasing prevalence of environmental pollutants has raised concerns about the...

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal ...

Morphological characterization and machine learning-based hyperspectral identification of naturally pigmented traditional Chinese starches.

As an intangible cultural heritage, food products derived from naturally pigmented traditional starc...

Physics-aware imaging AI for quantitative MASLD biomarker mapping: a systematic review of deep learning and radiomics across ultrasound, CT, and MRI.

OBJECTIVE: This systematic review critically appraises the current landscape of physics-aware artifi...

Adapt or specialize? A comprehensive evaluation of adapted SAM versus task-specific CNNs for fetal abdominal segmentation.

BACKGROUND: The fetal abdomen is crucial in prenatal screening, offering key insights into fetal gro...

Advances in antituberculosis drug-induced liver injury: Molecular mechanisms, genetic insights, and emerging animal-free prediction models.

Approximately 10 million tuberculosis patients worldwide require drug therapies annually. However, p...

An accurate, straightforward computer vision algorithm for optimal tumor-feeding visualization in cone-beam computed tomography hepatic arteriography: A preliminary study.

AIM: Although standardized 3D volume rendering techniques (VRT) and embolization guidance visualize ...

An Algorithm to Avoid Missed Bowel Injuries in Blunt Abdominal Trauma Patients.

UNLABELLED: Bowel injuries following blunt abdominal trauma (BAT) are evasive to detect clinically a...

Development and validation of a personalized web-based calculator of aggressive recurrence after surgery for early-stage hepatocellular carcinoma by machine learning.

BACKGROUND: Aggressive recurrence (AR) is an important factor affecting prognosis after surgery for ...

Artificial intelligence‑based quantitative analysis of hepatic fibrosis in carbon tetrachloride-induced mouse model of metabolic dysfunction-associated steatohepatitis.

UNLABELLED: Liver fibrosis, a major histopathological indicator of chronic liver injury, is also a k...

Detection of peritoneal, ovarian, and bowel endometriosis using FTIR spectroscopy and machine learning.

This study evaluated the diagnostic potential of Fourier-transform infrared (FTIR) spectroscopy comb...