Latest AI and machine learning research in gastroenterology for healthcare professionals.
Eimeria is a protozoan parasite that causes coccidiosis in various animal species, especially in chi...
PURPOSE: This systematic review examines the utility of deep learning algorithms in predicting patho...
This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/inte...
Artificial intelligence (AI) is transforming gastroenterology, particularly in endoscopy, which has ...
Quality of gastrointestinal endoscopy is a major determinant of its effectiveness. Artificial intell...
Artificial intelligence (AI) application in gastroenterology has grown in the last decade and contin...
The advent of artificial intelligence (AI) and deep learning algorithms, particularly convolutional ...
Natural language processing (NLP), a branch of artificial intelligence, has rapidly gained importanc...
OBJECTIVES: The objective is to develop and validate intratumoral and peritumoral ultrasomics models...
Spaceflight has several detrimental effects on human and rodent health. For example, liver dysfuncti...
Circular RNAs in extracellular vesicles (EV-circRNAs) are gaining recognition as potential biomarker...
With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-qu...
Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factor...
AIMS: Structured reporting in pathology is not universally adopted and extracting elements essential...
Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our p...
BACKGROUND: Laparoscopic cholecystectomy is the preferred treatment for symptomatic cholelithiasis a...
The integration of artificial intelligence (AI) in health care has the potential to enhance diagnost...
BACKGROUND: The automated classification of Helicobacter pylori infection status is gaining attentio...
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram ...
This study sought to establish and validate an interpretable CT radiomics-based machine learning mod...
Accurately extracting organs from medical images provides radiologist with more comprehensive eviden...