Gastroenterology

Liver Tumor Prediction using Attention-Guided Convolutional Neural Networks and Genomic Feature Analysis.

The task of predicting liver tumors is critical as part of medical image analysis and genomics area ...

Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.

We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP...

Enhancing diagnostic accuracy for HBV-related cirrhosis progression: predictive modeling using combined Golgi protein 73 and α1-microglobulin for the transition from nondecompensated to decompensated cirrhosis.

BACKGROUND AND AIMS: Chronic hepatitis B poses a major health risk, especially its progression to de...

Measurement of adipose body composition using an artificial intelligence-based CT Protocol and its association with severe acute pancreatitis in hospitalized patients.

BACKGROUND/OBJECTIVES: The clinical utility of body composition in predicting the severity of acute ...

Application of machine learning models to identify predictors of good outcome after laparoscopic fundoplication.

BACKGROUND: Laparoscopic fundoplication remains the gold standard treatment for gastroesophageal ref...

A risk prediction model for gastric cancer based on endoscopic atrophy classification.

BACKGROUNDS: Gastric cancer (GC) is a prevalent malignancy affecting the digestive system. We aimed ...

Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning.

BACKGROUND: Recent studies have suggested a potential association between gastric cancer (GC) and my...

A CT-based deep learning-driven tool for automatic liver tumor detection and delineation in patients with cancer.

Liver tumors, whether primary or metastatic, significantly impact the outcomes of patients with canc...

Comparison of MRI and CT based deep learning radiomics analyses and their combination for diagnosing intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) and other subtypes of primary liver cancer (PLC) have overlap...

Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM.

BACKGROUND: Chronic hepatitis B (CHB) is a common cause of liver cirrhosis (LC), a condition associa...

Letter to the editor regarding the article "learning curve for robot-assisted Mckeown esophagectomy in patients with thoracic esophageal cancer".

Reducing hepatitis C diagnostic disparities with a fully automated deep learning-enabled microfluidic system for HCV antigen detection.

Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C ...

Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers known to humans. However, ...

Development of machine learning-based differential diagnosis model and risk prediction model of organ damage for severe Mycoplasma pneumoniae pneumonia in children.

Severe Mycoplasma pneumoniae pneumonia (SMPP) poses significant diagnostic challenges due to its cli...

Multimodal treatment of colorectal liver metastases: Where are we? Current strategies and future perspectives.

Despite the continued high prevalence of colorectal cancer in the Western world, recent years have w...

The Performance of Artificial Intelligence in One Anastomosis Gastric Bypass Surgery: Comparative Efficacy of ChatGPT-4.0, ChatGPT-Omni, and Gemini AI.

BACKGROUND: The integration of artificial intelligence (AI) into medical practice opens up new front...

A semi-supervised convolutional neural network for diagnosis of pancreatic ductal adenocarcinoma based on EUS-FNA cytological images.

BACKGROUND: The cytological diagnostic process of EUS-FNA smears is time-consuming and manpower-inte...

Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).

BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpati...

Deep learning based on intratumoral heterogeneity predicts histopathologic grade of hepatocellular carcinoma.

OBJECTIVES: The potential of medical imaging to non-invasively assess intratumoral heterogeneity (IT...

Life's Crucial 9 and NAFLD from association to SHAP-interpreted machine learning predictions.

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. Car...

Machine learning for predicting metabolic-associated fatty liver disease including NHHR: a cross-sectional NHANES study.

OBJECTIVE: Metabolic - associated fatty liver disease (MAFLD) is a common hepatic disorder with incr...