Latest AI and machine learning research in gastroenterology for healthcare professionals.
Breast cancer liver metastasis (BCLM) presents a critical challenge in breast cancer treatment and has substantial epidemiological and clinical significance. Receptor status is pivotal in managing both primary breast cancer and its liver metastases. Moreover, shifts in these statuses can have a profound impact on patient treatment strategies and prognoses. Research has indicated that there is sign...
BACKGROUND AND AIMS: Inflammatory bowel diseases (IBD) are chronic conditions that can lead to a physical, social, and economic burden. Generative artificial intelligence (AI), particularly ChatGPT, gained attention for its potential to support medical practice. However, concerns remain about the reliability and consistency of its responses. This study systematically reviews the existing evidence ...
The generation of realistic medical images from text descriptions has significant potential to address data scarcity challenges in healthcare AI whi...
Colorectal cancer is one of the deadliest cancers today, but it can be prevented through early detection of malignant polyps in the colon, primarily...
Synthesizing medical images remains challenging due to limited annotated pathological data, modality domain gaps, and the complexity of representing...
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD), a chronic inflammatory disorder characterized by alcohol-independent hep...
The safety and efficacy of irreversible electroporation (IRE) in tumor therapy has been validated over many years by clinical application. An in-depth...
BACKGROUND: With the assistance of ENDOANGEL, a study was conducted at Hainan General Hospital to evaluate the effect of artificial intelligence (AI) ...
Inflammatory bowel disease (IBD), comprising ulcerative colitis and Crohn's disease, is a chronic inflammatory condition with global prevalence and va...
Accurate classification of focal liver lesions is crucial for diagnosis and treatment in hepatology. However, traditional supervised deep learning m...
We propose a multimodal spatiotemporal graph neural network (STG) framework to predict colorectal cancer liver metastasis (CRLM) progression. Curren...
Automatic segmentation of anatomical landmarks in endoscopic images can provide assistance to doctors and surgeons for diagnosis, treatments or medi...
In this issue of Developmental Cell, Yang et al. present an integrated experimental and computational platform that maps the spatiotemporal developmen...
Purpose To develop an artificial intelligence (AI) model based on gadoxetic acid-enhanced MRI to assist radiologists in hepatocellular carcinoma (HCC)...
Purpose To develop and validate a deep multitask network, MultiRecNet, for fully automatic prediction of disease-free survival (DFS) in patients with ...
BACKGROUND & AIMS: Enhanced computed tomography (CT) is the primary method for focal liver lesion diagnosis. We aimed to use automated machine learnin...
PURPOSE: To apply CT-based deep learning (DL) models for accurate solid debris-based classification of pancreatic fluid collections (PFC) in acute pan...
OBJECTIVE AND BACKGROUND: Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic rese...
BACKGROUND: The role of Blastocystis, a common intestinal parasitic protist of humans and other animals, in human health and disease remains elusive. ...