Gastroenterology

Pilot feasibility study of deep learning-based detection of malignant liver lesions in intraoperative ultrasound imaging.

BACKGROUND: Intraoperative ultrasound plays a central role in hepatobiliary surgery for the detection of liver lesions, but image interpretation is challenging and operator-dependent. Evidence supporting artificial intelligence-based detection tools in this setting remains limited. This study was designed as a preliminary pilot feasibility study of a future intraoperative support system for decisi...

Deep learning-based automatic identification model of main pancreatic duct in intraoperative ultrasonography.

BACKGROUND: Pancreatic enucleation (PE) preserves parenchyma in benign/low-grade malignant pancreatic tumors but risks postoperative pancreatic fistula (POPF) if the main pancreatic duct (MPD) is injured. Intraoperative ultrasound (IOUS) guides MPD localization, yet its efficacy is limited by operator dependency and expertise gaps. This study developed a deep learning (DL) model for automated MPD ...

Computational Toxicology Prioritization of CYP3A4 and DPP7 as Candidate Triclosan-Relevant Molecular Targets in Ulcerative Colitis.

Triclosan (TCS), a synthetic broad-spectrum antimicrobial classified as a novel persistent organic pollutant, is detected in over 75% of human urine s...

MRI radiomics combined with clinical factors to predict vessels encapsulating tumor clusters and early recurrence in hepatocellular carcinoma (≤ 3 cm).

OBJECTIVES: This study aims to develop a predictive model that combines MRI radiomics features with clinical factors to anticipate the preoperative pr...

Machine learning-guided discovery of spirocyclic inhibitors targeting Mycobacterium tuberculosis FtsZ.

Tuberculosis continues to pose serious threats to global public health and calls for the design of new drugs that can target key bacterial proteins. T...

Detection of hypodense hepatic and renal lesions on abdominal CT reconstructed with deep learning image reconstruction technique in patients with large body habitus: A multi-reader study.

PURPOSE: To evaluate detectability of hypodense hepatic and renal lesions on portal venous phase CT reconstructed with deep learning image reconstruct...

A morphology-guided ViT-CNN approach for the detection of lung and colon cancer using H&E-stained biopsy images.

The accurate categorisation of histopathological images is crucial for the reliable identification of morphologically similar cancers, including lung ...

Artificial intelligence-based prediction of claudin 18.2 expression and immune phenotype from routine histology to guide treatment decisions in patients with gastric cancer.

BACKGROUND: First-line treatment of gastric cancer is evolving with the integration of immune checkpoint inhibitors (ICIs) and targeted agents, compli...

Expression characteristics analysis, establishment of prognostic model and screening of key regulators based on selenium protein-related genes in rectal adenocarcinoma.

BACKGROUND: Selenium is an essential trace element in the human body and plays a significant role in multiple cancers. This study aims to comprehensiv...

Factors associated with delayed diagnosis of fibrotic interstitial lung disease: a retrospective cohort study.

BACKGROUND: Timely diagnosis and treatment of fibrotic interstitial lung disease (ILD) is crucial to preserve lung function and limit healthcare costs...

Comprehensive and low-cost machine learning models for predicting MASLD prevalence: cross-sectional evidence from the amol cohort study (AmolCS).

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a growing global health burden, yet early detection remains difficult, esp...

Machine learning prediction of increased healthcare utilization in colectomy for inflammatory bowel disease.

PURPOSE: Healthcare spending for patients with inflammatory bowel disease (IBD) has steadily increased over the past few decades. While some of the in...

Machine Learning-Assisted SERS Quantification of Sialylated Alpha-Fetoprotein: From Single-Cell Analysis to Hepatocellular Carcinoma Risk Assessment.

Sialylated alpha-fetoprotein (sAFP) is a very potential marker for the pathogenesis exploration and clinical assessment of hepatocellular carcinoma (H...

Evaluating the Accuracy of ChatGPT-4o in Addressing Complex Clinical Questions Based on NCCN Guidelines for Rectal Adenocarcinoma.

INTRODUCTION: The management of rectal adenocarcinoma requires navigation of complex, branching guideline pathways encompassing neoadjuvant sequencing...

Identification of exosome-related genes signature based on bioinformatics and machine learning for prognostic prediction in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor with increasing incidence and mortality rates worldwide. Exosomes are secretory ves...

A novel prognostic zinc finger gene model for hepatocellular carcinoma via machine learning.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly lethal malignancy with poor prognosis, and effective biomarkers for predicting immunotherapy re...

Single-cell spatial landscape of aggrephagy activity stratifies hepatocellular carcinoma neutrophils and delivers a 5-gene diagnostic panel for patient stratification.

BACKGROUND: Hepatocellular carcinoma (LIHC) features a complex tumor microenvironment (TME) where tumor-associated neutrophils (TANs) show significant...

Advances in CT and MRI for Yttrium-90 Radioembolization of Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Transarterial radioembolization (TARE) is increasingly used for patients with hepatocellular carcinoma (HCC) across Barcelon...

Curated endoscopic retrograde cholangiopancreatography images dataset.

Endoscopic Retrograde Cholangiopancreatography (ERCP) is a key procedure in the diagnosis and treatment of biliary and pancreatic diseases. Artificial...

From polyamine metabolism genes to immunoproteasome subunits: a transcriptome-based screening of candidate biomarkers in Crohn's disease.

This study explored Polyamine metabolism (PM)-related biomarkers and their regulatory processes in Crohn's disease (CD) using three transcriptome data...