Gastroenterology

An interpretable machine learning model for prediction of significant liver fibrosis in comorbid chronic hepatitis B and nonalcoholic fatty liver disease: a retrospective development and validation study.

Morphological subphenotypes of acute pancreatitis-related acute respiratory distress syndrome.

Deep Learning Analysis Based on Dual-energy CT-Derived Iodine Map for Predicting PD-L1 Expression in Gastric Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: PD-L1 expression is a critical biomarker in guiding immunotherapy for gastric cancer (GC). This study aims to investigate th...

Computer Aided Polyp Detection Multi-center International Randomized Controlled Study with a Focus on Community Clinics: GAIN Clinical Trial.

BACKGROUND/AIMS: Computer-aided polyp detection (CADe) systems can enhance polyp detection, although their performance has largely been evaluated at a...

Correlation of Automated in Vivo Image Quality With Radiologist's Performance in Abdomen Computed Tomography Across Conventional and Deep Learning Reconstructions.

OBJECTIVE: Image quality evaluation in radiology is most relevant when reflects radiologists' performance. This study assessed how image quality measu...

Application of deep learning on MRI for prognostic prediction in rectal cancer.

OBJECTIVES: Pretreatment MRI was employed to develop and validate a combined model integrating clinical features with deep learning for rectal cancer....

Biologically explicable multimodal model predicting local tumor progression and tumor invasiveness of hepatocellular carcinoma.

PURPOSE: Local tumor progression (LTP) of hepatocellular carcinoma (HCC) after thermal ablation (TA) is related to tumor invasiveness and threaten the...

A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features.

Viruses are a significant threat to human life, as demonstrated by the global COVID-19 pandemic and the Ebola outbreak. Diseases such as smallpox, AID...

Error in: Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis: Request for Correction.

Development of a machine learning model for predicting right-sided colon cancer recurrence: A retrospective single center pilot study.

INTRODUCTION AND AIM: Right-sided colon cancer (RSCC) is characterized by distinct clinical features and recurrence patterns. Our study aimed to devel...

Performance analysis of liver segmentation using nn-UNet TotalSegmentator: Focus on atypical livers, pathologies, and variants.

RATIONALE AND OBJECTIVES: This study evaluates the accuracy of the nn-UNet TotalSegmentator (TS) by Wasserthal et al. (2023) in segmenting atypical li...

Acute pancreatitis: mechanisms and therapeutic approaches.

Acute pancreatitis is a complex inflammatory condition characterized by sudden onset and rapid progression, with severe cases often associated with hi...

Gastric cancer organoids and their convergence in engineering approaches.

Gastric cancer research has rapidly progressed due to interdisciplinary advances in stem cell biology and bioengineering. Gastric organoid models, par...

Comprehensive review on immunotherapy for hepatocellular carcinoma: Current status and future perspectives.

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, remains a major global health concern due to its high incidence and mort...

AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.

BACKGROUND: Endoscopic diagnosis of Ampulla of Vater (AoV) lesions remains challenging owing to complex morphology and limited representative images, ...

Effectiveness of Machine Learning in Detecting Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

BACKGROUND: Vessels encapsulating tumor clusters (VETC) are significantly associated with poor prognosis in hepatocellular carcinoma (HCC). However, i...

Nerves Stimulates Crosstalk between Gastric Cancer and Group 3 Innate Lymphoid Cells to Enhance Immunosuppression.

The immunosuppressive tumor microenvironment (TME) enables cancer cells to evade clinical immunotherapies. Neural networks are vital components of the...

Impact of fine-grained learning rate configuration on the performance of medical image segmentation models.

Research on deep learning for medical image segmentation has shifted from single-modality networks to multimodal data fusion. Updating the parameters ...

Plasma proteomics biomarkers for predicting anti-tuberculosis drug-induced liver injury: A comprehensive assessment.

AIMS: This study aims to identify predictive plasma protein biomarkers for anti-tuberculosis drug-induced liver injury (ATB-DILI) and develop machine ...

Effect of Helicobacter pylori infection on deep learning-assisted detection of gastric neoplastic lesions under white light endoscopy.

BACKGROUND: Artificial intelligence (AI)-assisted endoscopy facilitates upper gastrointestinal lesion detection. Whether Helicobacter pylori (H. pylor...