Gastroenterology

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...

MKNet-family architectures for auto-segmentation of the residual pancreas after pancreatic resection: a deep learning comparative study.

PURPOSE: Accurate interpretation of CT scans after pancreatic resection is crucial for detecting abn...

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...

Colorectal Surgery Education in 2040.

The Accreditation Council for Graduate Medical Education (ACGME) recently conducted their 10-year sp...

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 ...

The "A-B-C" Classification Reveals Outcome Trajectories in Patients With Hepatocellular Carcinoma Under Atezolizumab/Bevacizumab.

BACKGROUND & AIMS: We aimed to identify subgroups of patients with unresectable hepatocellular carci...

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...