Gastroenterology

Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study.

BACKGROUND: The early diagnosis and treatment of Heliobacter pylori (H.pylori) gastrointestinal infe...

Aliado - A design concept of AI for decision support in oncological liver surgery.

BACKGROUND: The interest in artificial intelligence (AI) is increasing. Systematic reviews suggest t...

Machine learning for post-liver transplant survival: Bridging the gap for long-term outcomes through temporal variation features.

BACKGROUND: The long-term survival of liver transplant (LT) recipients is essential for optimizing o...

Polynomial-SHAP analysis of liver disease markers for capturing of complex feature interactions in machine learning models.

Liver disease diagnosis is pivotal for effective patient management, and machine learning techniques...

Real-time segmentation of biliary structure in pure laparoscopic donor hepatectomy.

Pure laparoscopic donor hepatectomy (PLDH) has become a standard practice for living donor liver tra...

Effectiveness of data-augmentation on deep learning in evaluating rapid on-site cytopathology at endoscopic ultrasound-guided fine needle aspiration.

Rapid on-site cytopathology evaluation (ROSE) has been considered an effective method to increase th...

ReBiA-Robotic Enabled Biological Automation: 3D Epithelial Tissue Production.

The Food and Drug Administration's recent decision to eliminate mandatory animal testing for drug ap...

Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques.

The study of fetal gut development is critical due to its substantial influence on immediate neonata...

Machine learning algorithms and biomarkers identification for pancreatic cancer diagnosis using multi-omics data integration.

PURPOSE: Pancreatic cancer is a lethal type of cancer with most of the cases being diagnosed in an a...

Raman fiber-optic probe for rapid diagnosis of gastric and esophageal tumors with machine learning analysis or similarity assessments: a comparative study.

Gastric and esophageal cancers, the predominant forms of upper gastrointestinal malignancies, contri...

Bowel preparation before elective right colectomy: Multitreatment machine-learning analysis on 2,617 patients.

BACKGROUND: In the worldwide, real-life setting, some candidates for right colectomy still receive n...

Personalized food consumption detection with deep learning and Inertial Measurement Unit sensor.

For individuals diagnosed with diabetes mellitus, it is crucial to keep a record of the carbohydrate...

Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

Randomized controlled trial of an artificial intelligence diagnostic system for the detection of esophageal squamous cell carcinoma in clinical practice.

BACKGROUND: Artificial intelligence (AI) has made remarkable progress in image recognition using dee...

Real-time augmentation of diagnostic nasal endoscopy video using AI-enabled edge computing.

AI-enabled augmentation of nasal endoscopy video images is feasible in the clinical setting. Edge co...

Effectiveness of artificial intelligence assisted colonoscopy on adenoma and polyp miss rate: A meta-analysis of tandem RCTs.

BACKGROUND AND AIMS: One-fourth of colorectal neoplasia is missed at screening colonoscopy, represen...

Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.

BACKGROUND: Hepatocellular carcinoma (HCC) is highly aggressive, with delayed diagnosis, poor progno...

Artificial Intelligence in Gastrointestinal Endoscopy.

Recent advancements in artificial intelligence (AI) have significantly impacted the field of gastroi...

Identification of macrotrabecular-massive hepatocellular carcinoma through multiphasic CT-based representation learning method.

BACKGROUND: Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive subt...

Identification of four novel acute-on-chronic liver failure clusters with distinct clinical trajectories and mortality using machine learning methods.

BACKGROUND AND AIMS: Machine learning (ML) can identify the hidden patterns without hypothesis in he...

Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy i...