Gastroenterology

Revealing the anti-tumor mechanisms of aromatic oil from Amomum villosum through integrated network pharmacology, bioinformatics, machine learning, single-cell sequencing, and cell experiments.

The dry fruits of Amomum villosum (Av) are a traditional Chinese medicine used for gastrointestinal ...

Integrative analysis of transcriptomic data reveals a predictive gene signature for chemoradiotherapy response in rectal cancer.

Locally advanced rectal cancer (LARC) is treated with neoadjuvant chemoradiotherapy (nCRT), but only...

A filter-level explainability framework for CNNs in histopathology image analysis.

Convolutional neural networks (CNNs) have achieved remarkable accuracy in histopathology image class...

AI-Based Exhaled VOC Panels as Gut Microbiota-Derived Biomarkers for IBD Screening.

Inflammatory bowel diseases (IBD) present significant diagnostic and therapeutic challenges due to t...

Decipher the molecular network of PFOA in inflammatory bowel disease through integrating machine learning, molecular docking strategies, and validation in vitro.

OBJECTIVE: Perfluorooctanoic Acid (PFOA), widely recognized as an enduring environmental pollutant, ...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vascula...

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI f...

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for sever...

Synergistic impact of insulin resistance and hepatic fibrosis on cardiovascular events in patients with coronary artery disease: A machine learning subtyping and interaction analysis.

BACKGROUND AND AIMS: Insulin resistance (IR) and hepatic fibrosis are significant yet underexplored ...

Real-world evidence in metabolic dysfunction-associated steatotic liver disease (MASLD): insights, challenges, and future directions.

Real-world evidence (RWE), derived from real-world data, offers key insights into metabolic dysfunct...

Emerging nanoparticle-based therapies for pancreatic cancer: Current clinical landscape.

Pancreatic cancer, particularly ductal adenocarcinoma (PDAC) is one of the most aggressive and letha...

Toxicophore-informed machine learning integrating Tox21 assay readouts for organ system-specific carcinogenicity prediction.

Accurate identification of carcinogenic hazards is essential for public health protection, yet tradi...

Revolutionizing Liver Imaging: Artificial Intelligence-Driven Advances in Diagnostics and Staging.

Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhance...

MethylMSI: Prediction of microsatellite instability based on DNA methylation profile and SVM model.

Microsatellite instability (MSI) has gained increasing attention as a promising biomarker for cancer...

A Simple Laboratory-based Machine Learning Model Accurately Predicts Advanced Liver Fibrosis in Metabolic Dysfunction-associated Steatotic Liver Disease Patients.

BACKGROUND/AIM: Metabolic dysfunction-associated steatotic liver disease (MASLD) is often silent and...

Machine learning-based binary classification of elevated HbA1c (≥6.5 %) for risk assessment.

OBJECTIVE: One of the most important biomarkers for evaluating long-term glycemic management and est...

Artificial intelligence-driven 3-dimensional simulation system for enhanced preoperative planning in gastric cancer surgery: a retrospective validation study.

BACKGROUND: Few studies have developed artificial intelligence (AI) systems for the automatic recogn...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for op...

AI-powered intestinal ultrasound in inflammatory bowel disease: Advancing toward automated disease assessment.

The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close m...

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

Meta-analysis of faecal microbiome studies followed by machine learning to identify intestinal disease-specific taxonomic signatures.

Alterations in the gut microbiome have been found to be associated with both inflammatory bowel dise...