Gastroenterology

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

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ChatExosome: An Artificial Intelligence (AI) Agent Based on Deep Learning of Exosomes Spectroscopy for Hepatocellular Carcinoma (HCC) Diagnosis.

Large language models (LLMs) hold significant promise in the field of medical diagnosis. There are s...

Deliod a lightweight detection model for intestinal organoids based on deep learning.

Intestinal organoids are indispensable tools for exploring intestinal disorders. Deep learning metho...

Artificial intelligence-assisted diagnosis of early gastric cancer: present practice and future prospects.

Gastric cancer (GC) occupies the first few places in the world among tumors in terms of incidence an...

Human sleep position classification using a lightweight model and acceleration data.

PURPOSE: This exploratory study introduces a portable, wearable device using a single accelerometer ...

Comparative performance of multiple ensemble learning models for preoperative prediction of tumor deposits in rectal cancer based on MR imaging.

Ensemble learning can effectively mitigate the risk of model overfitting during training. This study...

Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major ...

Evaluation of an artificial intelligence-based system for real-time high-quality photodocumentation during esophagogastroduodenoscopy.

Complete and high-quality photodocumentation in esophagoduodenogastroscopy (EGD) is essential for ac...

A deep learning-driven method for safe and effective ERCP cannulation.

PURPOSE: In recent years, the detection of the duodenal papilla and surgical cannula has become a cr...

Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer.

BACKGROUND: Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after su...

Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.

BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). ...

A foundation systematic review of natural language processing applied to gastroenterology & hepatology.

OBJECTIVE: This review assesses the progress of NLP in gastroenterology to date, grades the robustne...

Explainable Classification of Benign-Malignant Pulmonary Nodules With Neural Networks and Information Bottleneck.

Computerized tomography (CT) is a clinically primary technique to differentiate benign-malignant pul...

Use of artificial intelligence in submucosal vessel detection during third-space endoscopy.

While artificial intelligence (AI) shows high potential in decision support for diagnostic gastroint...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to pre...

Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.

Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly impro...

Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most prevalent and deadly form of liver cancer, and its mortal...

Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer.

Gastric cancer (GC) is one of the most common tumors; one of the reasons for its poor prognosis is t...

Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques.

In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and ma...

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