Gastroenterology

Benzo[a]pyrene promotes gastric cancer progression via activation of the Correa cascade through modulation of the STAT3-TP53-MMP9 molecular axis.

To investigate the role of Benzo[a]pyrene (BaP) in driving the Correa cascade during gastric cancer ...

Minimum Clinically Achievable Dose for Detecting Liver Lesions Using Deep Learning Image Reconstruction: A Phantom and Patient Study.

RATIONALE AND OBJECTIVES: To investigate the performance of deep learning image reconstruction (DLIR...

A Multiomic Liquid Biopsy for the Earlier Detection of Colorectal Cancer.

UNLABELLED: Timely diagnosis and intervention in colorectal cancer are critical to improving patient...

Early recurrence prediction and risk stratification of hepatocellular carcinoma after transarterial chemoembolization achieving imaging complete response based on contrast-enhanced CT machine learning.

OBJECTIVES: To develop and validate machine learning (ML) models using clinical and contrast-enhance...

Characterization of Kidney and Liver Cystic Phenotype Associated with GANAB Using Advanced Imaging Biomarkers.

UNLABELLED: : Background and Hypothesis: Monoallelic pathogenic variants in GANAB cause autosomal do...

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis.

One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic condit...

Proteomics-based machine learning model for predicting secondary infection in HBV-related liver failure.

Patients with Hepatitis B Virus-related liver failure are highly vulnerable to secondary infections ...

Predicting short-term mortality in severe cirrhosis: An interpretable machine learning model integrating routine clinical indicators.

BACKGROUND: The critical need for precise risk stratification in severe liver cirrhosis is underscor...

Multi-omics profiling reveals cholic acid-mediated immunosuppression driven by peritumoral ductular reactions in hepatocellular carcinoma.

Hepatocellular carcinoma remains a leading cause of cancer mortality worldwide, with peritumoral mic...

Application of a Natural Language Processing Framework for Data Extraction From Pathology Reports Across Multiple Cancer Types.

BACKGROUND: Pathological reports provide comprehensive insights into the clinical and pathological f...

A CT radiomics signature enables risk stratification and survival prediction in colorectal liver metastases.

Colorectal liver metastases (CRLM) represent a major clinical challenge because outcomes after hepat...

A fully automated workflow for the digital image analysis of the intestinal microcolony survival assay.

Preoperative prediction of metachronous liver metastasis in colorectal cancer using a deep learning-based radiomics model with automatic segmentation: a multicenter study.

OBJECTIVES: To develop and validate an integrated clinical-radiomics nomogram predicting the risk of...

Artificial Intelligence as a New Player in Dietary Management of Inflammatory Bowel Disease.

Virtual Multi-Phase Contrast Enhanced Liver MRI Using Deep Learning for Evaluating Hepatocellular Carcinoma.

A deep learning (DL) model was developed to generate contrast-enhanced MRI (CE-MRI) at multiple enha...

A Deep Learning Algorithm for Liver Metastasis Detection at Contrast-enhanced Abdominal CT in Patients with Colorectal Cancer: A Comparative Study with Radiologists.

Purpose To evaluate the performance of a deep learning algorithm (DLA) for detecting liver metastase...

A Network-Based Association of IBD and Colorectal Cancer Using Proteomics Data.

BACKGROUND: Colorectal cancer (CRC) is a major cause of morbidity and mortality, with chronic inflam...

Pediatric Personalized Deep Learning Models for Segmentation of Hepatoblastoma at CT and MRI.

Purpose To evaluate the generalizability of adult-trained models for hepatoblastoma segmentation to ...

Impact of Annotation Level on Multisequence MRI Models for Preoperative Microvascular Invasion Prediction in Hepatocellular Carcinoma.

Purpose To evaluate the performance of deep learning models integrating multimodal data for predicti...

Identification and Validation of cGAS-STING Pathway-Associated Predictive and Therapeutic Models for Esophageal Squamous Cell Cancer Patients via Artificial Intelligence and Multi-Omics.

BACKGROUND: Esophageal squamous cell cancer (ESCC) is a malignancy derived from the Esophagus, and d...

Generalizability of deep learning-based dose conversion model in proton beam therapy.

BACKGROUND: In proton beam therapy (PBT), the analytical pencil beam (PB) algorithm involves dose un...