Latest AI and machine learning research in gastroenterology for healthcare professionals.
BACKGROUND: Functional gastrointestinal disorders (FGIDs), as a group of syndromes with no identifie...
Intraoperative identification of malignancies using indocyanine green (ICG)-based fluorescence imagi...
BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of ...
The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forc...
Over the past few years, developments in artificial intelligence (AI), especially in radiomics and d...
Genetic association studies have identified hundreds of independent signals associated with type 2 d...
BACKGROUND: We evaluated the outcomes of a robotic pancreaticoduodenectomy (RPD) program implemented...
PURPOSE: Deep neural networks need to be able to indicate error likelihood via reliable estimates of...
This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptiv...
PURPOSE: To evaluate the effectiveness of automated liver segmental volume quantification and calcul...
BACKGROUND: In recent years, computer-assisted intervention and robot-assisted surgery are receiving...
The anti-obesity potential of probiotics has been widely reported, however their utilization in high...
BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been conf...
INTRODUCTION: At our institute, we usually perform robot-assisted surgery for rectal cancer as minim...
The adoption of minimally invasive techniques for hepatocellular resection has progressively increas...
OBJECTIVES: To evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in c...
BACKGROUND: Systemic inflammatory response represented by C-reactive protein and albumin ratio (CAR)...
AIMS: A strong association between fatty liver disease (FLD) and coronary artery disease is consiste...