Gastroenterology

Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches.

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits pronounced heterogeneity, which significantly limits the effectiveness of precision therapies. A comprehensive understanding of the biological characteristics and molecular mechanisms underlying HCC cell subpopulations is crucial for improving prognostic predictions and refining treatment strategies.

Deep ensemble framework with Bayesian optimization for multi-lesion recognition in capsule endoscopy images.

In order to address the challenges posed by the large number of images acquired during wireless capsule endoscopy examinations and fatigue-induced leakage and misdiagnosis, a deep ensemble framework is proposed, which consists of CA-EfficientNet-B0, ECA-RegNetY, and Swin transformer as base learners. The ensemble model aims to automatically recognize four lesions in capsule endoscopy images, inclu...

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses.

BACKGROUND: Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enhanced ribosome biogenesis may be associated with tu...

National Guidelines for Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in Peritoneal Malignancies: A Worldwide Systematic Review and Recommendations of Strength Analysis.

BACKGROUND: National guidelines (GLs) for surgical cytoreduction (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) in the management of peri...

Developing a ground truth for a convolutional neural network-based segmentation of anatomical structures in endoscopic ear surgery videos.

OBJECTIVE: This study aimed to develop a ground truth for a convolutional neural network-based segmentation of the stapes, chorda tympani and facial n...

Unmet needs in autoimmune liver diseases.

Autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis are well-defined autoimmune liver diseases, the pathophysiology ...

Leveraging automated machine learning to predict colon cancer prognosis from clinical features and risk groups: a retrospective cohort study.

BACKGROUND: Predicting colon cancer recurrence is crucial for determining the need for adjuvant therapy after curative resection. However, clinical de...

CDKN1A and EGR1 are key genes for endoplasmic reticulum stress-induced ferroptosis in MASH.

Metabolic dysfunction-associated steatohepatitis (MASH) is a complex liver disease whose pathogenesis involving endoplasmic reticulum (ER) stress and ...

Recent advancement in size measurement during endoscopy.

Accurate lesion size measurement is essential in endoscopic practice as it influences treatment strategies, surveillance decisions, and clinical outco...

Guideline-driven clinical decision support for colonoscopy patients using the hierarchical multi-label deep learning method.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic...

Characteristic genes and immune infiltration analysis of gastric cancer based on bioinformatics analysis and machine learning.

BACKGROUND: Gastric cancer (GC), a common and deadly malignancy worldwide, is a serious burden on society and individuals. However, available diagnost...

Unveiling the role of IL7R in metabolism-associated fatty liver disease leading to hepatocellular carcinoma through transcriptomic and machine learning approaches.

Dysregulation of hepatic metabolism is a crucial factor in the development of fatty liver disease and significantly increases the risk of hepatocellul...

Mechanisms underlying obesity-malignancy connection: a systematic narrative review.

The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellul...

Development and validation of a hypoxemia prediction model in middle-aged and elderly outpatients undergoing painless gastroscopy.

Hypoxemia is a common complication associated with anesthesia in painless gastroscopy. With the aging of the social population, the number of cases of...

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study.

OBJECTIVES: Pancreatic cancer treatment plans involving surgery and/or chemotherapy are highly dependent on disease stage. However, current staging sy...

Evaluation of a deep-learning segmentation model for patients with colorectal cancer liver metastases (COALA) in the radiological workflow.

OBJECTIVES: For patients with colorectal liver metastases (CRLM), total tumor volume (TTV) is prognostic. A deep-learning segmentation model for CRLM ...

Deep Learning and Radiomic Signatures Associated with Tumor Immune Heterogeneity Predict Microvascular Invasion in Colon Cancer.

RATIONALE AND OBJECTIVES: This study aims to develop and validate a deep learning radiomics signature (DLRS) that integrates radiomics and deep learni...

Investigating the Mechanisms of Pazopanib-induced Hepatotoxicity: Insights from Network Toxicology, Microarray Analysis, and Machine Learning.

BACKGROUND: Pazopanib is an oral multi-kinase inhibitor that is effective in treating various tumors. However, it is commonly associated with hepatoto...

Innate immune cell barrier-related genes inform precision prognosis in pancreatic cancer.

INTRODUCTION: Pancreatic cancer (PC) remains a lethal malignancy with limited treatment options. The role of innate immune cell barrier-related genes ...

Cardiovascular, Kidney, Liver, and Metabolic Interactions in Heart Failure: Breaking Down Silos.

Over the past few decades, the rising burden of metabolic disease, including type 2 diabetes, prediabetes, obesity, and metabolic dysfunction-associat...