Gastroenterology

Percutaneous endoscopic interlaminar discectomy in patients with lumbar disc herniation: risk factors and thresholds for adverse outcomes.

BACKGROUND: Percutaneous endoscopic interlaminar discectomy (PEID) is a common surgical technique for lumbar disc herniation (LDH), but the risk factors for adverse outcomes remain controversial. This study aims to develop and validate a predictive model based on machine learning algorithms to identify key clinical indicators influencing adverse outcomes after PEID. METHODS: This retrospective stu...

Identification of PTPRR gene associated with cirrhosis and sarcopenia based on bioinformatics and machine learning.

BACKGROUND: Cirrhosis and sarcopenia frequently coexist and are associated with poor clinical outcomes; however, their shared genetic basis remains incompletely understood. METHODS: We applied conditional and conjunctional false discovery rate (cFDR/ccFDR) analyses to genome-wide association study (GWAS) summary statistics for cirrhosis and sarcopenia-related traits, including appendicular lean ma...

Transcriptomic Analysis of Shared Lipid Metabolism in Chronic Hepatitis B and Non-Alcoholic Fatty Liver Disease Using Weighted Gene Expression Network Analysis.

Chronic hepatitis B (CHB) and non-alcoholic fatty liver disease (NAFLD) frequently coexist, and lipid metabolic dysregulation may represent a shared b...

Innovations in Gastric Cancer Surgery During Early Minimally Invasive Era and Future Perspectives.

The landscape of gastric cancer surgery has undergone remarkable transformation, evolving from traditional open procedures to the modern era of live-s...

Single-cell and bulk omics uncover fibroblast heterogeneity and HSPH1 as a key driver in Barrett's esophagus to esophageal adenocarcinoma progression.

BACKGROUND: Esophageal adenocarcinoma (EAC) is a highly aggressive malignancy with poor prognosis, often evolving from Barrett's esophagus (BE). Under...

Dynamic machine learning model integrating resting energy expenditure for predicting postoperative complications after gastrectomy for gastric cancer.

PURPOSE: To investigate whether perioperative resting energy expenditure (REE) dynamics improve prediction of postoperative complications after gastre...

STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.

Spatial transcriptomics provides high-throughput measurement of gene expression while retaining spatial context; however, inferring accurate cell-type...

Development of a machine learning-based prognostic prediction model and a web-based tool for pediatric hepatoblastoma: a Surveillance, Epidemiology, and End Results (SEER) database study.

BACKGROUND: Prognostic evaluation of pediatric hepatoblastoma (HB) remains challenging due to the low accuracy of traditional risk stratification mode...

Clinician engagement shapes the impact of AI-based ECG screening for chronic liver disease in primary care.

Artificial intelligence (AI)-based screening tools show promise for early identification of chronic liver disease (CLD), yet their effectiveness in re...

A human-AI collaborative workflow for improved gross tumor volume delineation in esophageal cancer radiotherapy.

BACKGROUND: Esophageal cancer tumors exhibit complex and variable distribution. Due to differences in clinical experience, junior oncologists often sh...

Exploring the prognostic role of senescence-related genes in gastric cancer through multi-omics integration and machine learning.

Cellular senescence plays a context-dependent role in gastric cancer (GC), functioning both through tumor-suppressive arrest and the tumor-promoting s...

Deep learning based on CD3 histological slides for prediction of colon cancer outcome: analysis of three international stage III colon cancer cohorts.

Prognostic stratification in stage III colon cancer remains poor, despite treatment advances. Tumor-infiltrating lymphocytes, particularly CD3+ T cell...

Deep learning reconstruction for liver DWI: impact on image quality and ADC quantification.

PURPOSE: To assess the image quality, apparent diffusion coefficient (ADC) values, and lesion detection of diffusion-weighted imaging (DWI) with compr...

Molecular basis of precision nutrition: Food components, microbiome-derived metabolites, and multi-omics modeling.

Metabolic disorders, including obesity, type 2 diabetes, metabolic syndrome, and fatty liver disease, reflect multifactorial interactions among diet, ...

Development of Models for Predicting the 7-Month Risk of Venous Thromboembolism and Clinically Relevant Bleeding in Ambulatory Patients with Cancer: Analysis from the AVERT Trial.

BACKGROUND: Patients with cancer are at elevated risk of venous thromboembolism (VTE). While primary thromboprophylaxis reduces VTE incidence, it also...

Electrochemical Biosensors for Hepatocellular Carcinoma: Advances, Analytical Performance, and Clinical Translation.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide due to the limited sensitivity of current surveillance an...

Artificial intelligence-assisted confocal laser endomicroscopy for predicting invasion depth of superficial esophageal mucosal lesions: a cohort study.

INTRODUCTION: Accurate assessment of invasion depth in esophageal squamous cell carcinoma (ESCC) is essential for optimal treatment. Probe-based confo...

Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.

BACKGROUND: Emergency ventral hernia repair remains a challenging procedure due to patient instability, contaminated surgical fields, and heterogeneit...

Electronics-free soft robotic minitablet for on-demand gastric molecular sensing and diagnostics in vivo.

Real-time biomarker sensing and molecular sampling in the stomach can transform how gastrointestinal disorders are diagnosed and managed-yet integrati...

Predicting endoscopic third ventriculostomy with choroid plexus cauterization success with machine learning: the importance of ventricle size and the irrelevance of etiology.

OBJECTIVE: Endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) has decreased rates of shunt dependence in infants with hydroc...