Gastroenterology

Identifying Post-Surgical Recurrence Subtype of T1 Stage Colorectal Cancer by Machine Learning.

INTRODUCTION: Traditional risk stratification heavily relies on expert judgment and manually established thresholds. This study aims to automatically identify subtypes in the patients of T1-stage colorectal cancer with distinct clinicopathologic characteristics and recurrence risk profiles, using machine learning. METHODS: We analyzed data from 3,367 patients (mean follow-up, 1281 days) with T1 co...

A novel integrative machine learning-based prognostic model reveals lactylation regulation in hepatocellular carcinoma progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant liver tumor with poor clinical outcomes. Accumulated evidence has demonstrated lactylation plays a vital role in the metabolic reprogramming. However the mechanisms underlying the role of lactylation in the regulation of HCC progression remain largely unknown. This study aims to construct a prognostic model based on lac...

Integrative bioinformatics and experiments identify RIBC2 as a key regulator in the esophageal cancer.

Early detection of esophageal cancer (EC) remains a major challenge due to the limited understanding of its initial molecular alterations. Therefore, ...

Classification of liver tissue pathological changes via optical biopsy based on refractive index sensing.

Optical biopsy enables minimally invasive, quantitative tissue assessment, yet clinically useful implementations require rapid and objective decision-...

Trichosanthes kirilowii extract alleviated liver fibrosis and acute myocardial infarction by inhibiting VCAN to restrain monocyte senescence: Insights from bioinformatic analyses and experimental validation.

BACKGROUND: Liver fibrosis and acute myocardial infarction (AMI) tended to co-occur. Cellular senescence and an imbalanced immune microenvironment wer...

Development of a hybrid deep learning-based framework for liver fibrosis classification using ultrasound images.

BACKGROUND AND AIMS: Liver fibrosis is a progressive accumulation of extracellular matrix proteins with distortion of hepatic architecture and can pro...

Development and validation of a machine learning stratified prediction model for early warning of anti-tuberculosis drug-induced liver injury risk based on real-world data: a retrospective cohort study.

OBJECTIVE: This study aimed to develop and validate stratified machine learning models for early prediction of anti-tuberculosis drug-induced liver in...

Integrative analysis of immune and microbial subtypes predicts immunotherapy response in stomach adenocarcinoma.

The tumor immune microenvironment and intratumoral microbiota play critical roles in cancer progression and immunotherapy response, yet their integrat...

Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.

Colorectal cancer (CRC) is the third most common malignancy worldwide, and early detection is vital to prevent metastasis and postoperative recurrence...

Clinical Impact of Artificial Intelligence-Augmented Lymph Node Evaluation in Metastatic Gastric, Colorectal, and Breast Cancer.

CONTEXT.—: Lymph node (LN) assessment plays a critical role in cancer staging and prognosis but remains a time-consuming and labor-intensive task in p...

Explainable AI-based analysis of human pancreas sections identifies traits of type 2 diabetes.

Type 2 diabetes (T2D) is a chronic disease currently affecting around 500 million people worldwide with often severe health consequences. Yet, histopa...

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. However, the patient group undergoing liver transplantat...

Biomarker discovery and drug repurposing in hepatocellular carcinoma through transcriptomics, machine learning, network pharmacology, and molecular dynamics.

This study employed an integrative computational and systems biology framework to define a diagnostic gene signature for hepatocellular carcinoma (HCC...

UriPred: Machine learning prediction of urinary proteins and identification of biomarkers for liver cancer.

Urinary proteins are promising non-invasive biomarkers, but their low abundance and wide dynamic range make detection challenging. This study presents...

Targeting the MPO/LCN2/GMPPB axis in IBS-depression comorbidity: Integrated multi-omics and bidirectional network pharmacology for precision diagnostics and therapeutics.

BACKGROUND: Irritable Bowel Syndrome (IBS) and Major Depressive Disorder (MDD) exhibit high comorbidity, driven by dysregulation of gut-brain axis int...

Integrating multi-omics analysis identifies DNA damage-related gene CLSPN as a biomarker in gastric cancer.

DNA damage exhibits a strong correlation with gastric cancer (GC). However, there is still a paucity of comprehensive, in-depth investigations into th...

Spectral CT-derived extracellular volume fraction for pathological characterization and noninvasive T staging in colon cancer.

OBJECTIVES: To investigate the association between the extracellular volume fraction (ECV) quantified by spectral CT and multiparameter pathological f...

Quantitative Real-Time MRI for the Assessment of Gastric Motility.

BACKGROUND: Current reference standards for measuring gastric emptying and motility are not considered optimal due to the time required, ionizing radi...

Pharmacological Nuances and Epigenetic Precision: Critical Additions to Plasma Protein-Targeted IBD Research.

A machine learning model for predicting 28-day mortality in patients with alcoholic cirrhosis and sepsis: a study based on the MIMIC-IV database.

OBJECTIVE: To develop and validate the best machine learning model for predicting 28-day mortality in septic patients with alcoholic cirrhosis (AC), l...