Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning.

OBJECTIVE: To develop and validate a novel diagnostic model for detecting bacterial infections in pa...

A hybrid XAI-driven deep learning framework for robust GI tract disease diagnosis.

The stomach is one of the main digestive organs in the GIT, essential for digestion and nutrient abs...

A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.

Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk ...

CFM-UNet: coupling local and global feature extraction networks for medical image segmentation.

In medical image segmentation, traditional CNN-based models excel at extracting local features but h...

Comparison of AI chatbot predicted and realworld survival outcomes in hepatocellular carcinoma.

This study compares survival predictions made by an artificial intelligence (AI) based chatbot with ...

Radiomics analysis based on dynamic contrast-enhanced MRI for predicting early recurrence after hepatectomy in hepatocellular carcinoma patients.

This study aimed to develop a machine learning model based on Magnetic Resonance Imaging (MRI) radio...

Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms.

This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in he...

Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant thre...

Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy.

Helicobacter pylori (HP) have chronically infected more than half of the world's population and is a...

A novel approach to overcome black box of AI for optical diagnosis in colonoscopy.

Accurate real-time optical diagnosis that distinguishes neoplastic from non-neoplastic colorectal le...

Deep learning model for grading carcinoma with Gini-based feature selection and linear production-inspired feature fusion.

The most common types of kidneys and liver cancer are renal cell carcinoma (RCC) and hepatic cell ca...

Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy.

Metabolic homeostasis requires engagement of catabolic and anabolic pathways consuming nutrients tha...

Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer.

Pancreatic cancer (PC), often referred to as the "king of cancers", has demonstrated limited success...

Unveiling the mechanisms and promising molecular targets of curcumin in pancreatic cancer through multi-dimensional data.

Pancreatic cancer (PC) is a highly aggressive and fatal malignancy, primarily affecting older males....

Enhancing ultrasonographic detection of hepatocellular carcinoma with artificial intelligence: current applications, challenges and future directions.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality world...

A novel artificial intelligence-based system for quality monitoring during esophagogastroduodenoscopy: a multicenter randomized controlled study.

Esophagogastroduodenoscopy (EGD) is the pivotal procedure for diagnosis of upper gastrointestinal (U...

Machine learning based obesity and aging related signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is one of most common cancers with high invasiveness and p...

Harnessing artificial intelligence for detection of pancreatic cancer: a machine learning approach.

PURPOSE: Pancreatic cancer (PC) is one of the most lethal malignancies, often presenting with nonspe...

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