Gastroenterology

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

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Deep Learning and Automatic Differentiation of Pancreatic Lesions in Endoscopic Ultrasound: A Transatlantic Study.

INTRODUCTION: Endoscopic ultrasound (EUS) allows for characterization and biopsy of pancreatic lesio...

Applying Deep-Learning Algorithm Interpreting Kidney, Ureter, and Bladder (KUB) X-Rays to Detect Colon Cancer.

Early screening is crucial in reducing the mortality of colorectal cancer (CRC). Current screening m...

Is ChatGPT-4 a Reliable Tool in Autoimmune Hepatitis?

INTRODUCTION: Artificial intelligence-based chatbots offer a potential avenue for delivering persona...

Diagnosis of Pancreatic Ductal Adenocarcinoma Using Deep Learning.

Recent advances in artificial intelligence (AI) research, particularly in image processing technolog...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and t...

The role of aspirin in preventing gastrointestinal cancers.

Cancer remains an increasing global health issue and is projected to cause 50% of all global deaths ...

The Role of Artificial Intelligence and Big Data for Gastrointestinal Disease.

Artificial intelligence (AI) is a rapidly evolving presence in all fields and industries, with the a...

Past, Present, and Future: A History Lesson in Artificial Intelligence.

Over the past 5 decades, artificial intelligence (AI) has evolved rapidly. Moving from basic models ...

Advancements in early detection of pancreatic cancer: the role of artificial intelligence and novel imaging techniques.

Early detection is crucial for improving survival rates of pancreatic ductal adenocarcinoma (PDA), y...

WISE: Efficient WSI selection for active learning in histopathology.

Deep neural network (DNN) models have been applied to a wide variety of medical image analysis tasks...

Predicting Portal Pressure Gradient in Patients with Decompensated Cirrhosis: A Non-invasive Deep Learning Model.

BACKGROUND: A high portal pressure gradient (PPG) is associated with an increased risk of failure to...

Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.

PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular ...

The use of artificial intelligence in colonoscopic evaluations.

PURPOSE OF REVIEW: This review aims to highlight the transformative impact of artificial intelligenc...

Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

PURPOSE: Although noninvasive tests can be used to predict liver fibrosis, their accuracy is limited...

A novel endoscopic artificial intelligence system to assist in the diagnosis of autoimmune gastritis: a multicenter study.

BACKGROUND:  Autoimmune gastritis (AIG), distinct from Helicobacter pylori-associated atrophic gastr...

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study.

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, a...

Clinical evaluation of accelerated diffusion-weighted imaging of rectal cancer using a denoising neural network.

BACKGROUND: To evaluate the effectiveness of a deep learning denoising approach to accelerate diffus...

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