Latest AI and machine learning research in gastroenterology for healthcare professionals.
Natural language processing (NLP)-based data extraction from electronic health records (EHRs) holds...
BACKGROUND: Patients with alpha-fetoprotein (AFP)-positive hepatocellular carcinoma (HCC) have aggre...
BACKGROUND: Primary pancreatic signet ring cell carcinoma (PSRCC), an extremely rare histologic vari...
Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identificatio...
BACKGROUND: Currently, automatic esophagus segmentation remains a challenging task due to its small ...
BACKGROUND AND STUDY AIM: High-definition virtual chromoendoscopy, along with targeted biopsies, is ...
BACKGROUND: Clinical decision-making in gastrointestinal surgery is complex due to the unpredictabil...
PURPOSE: The debate surrounding factors influencing postoperative flatus and defecation in patients ...
Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to dev...
The heterogeneity of Hepatocellular Carcinoma (HCC) poses a barrier to effective treatment. Stratify...
BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate o...
Using a systematic literature search of original articles published during 2023 in Gastrointestinal ...
PURPOSE: To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment...
Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in...
BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemothe...
Artificial intelligence (AI) is a rapidly growing field with significant implications for radiology....
Technological advancements in laryngology, broncho-esophagology, and sleep surgery have enabled the ...
PURPOSE: The aim of this study is to develop a deep learning model capable of discriminating between...
BACKGROUND: We developed an artificial intelligence (AI)-based endoscopic ultrasonography (EUS) syst...
BACKGROUND AND OBJECTIVES: Deep learning models (DLMs) are applied across domains of health sciences...
In recent times, time-to-event data such as time to failure or death is routinely collected alongsid...