Latest AI and machine learning research in gastroenterology for healthcare professionals.
This study aimed to discuss the application value of the bias field correction algorithm in magnetic...
OBJECTIVE: This study aimed to evaluate the reliability of liver and spleen Hounsfield units (HU) me...
Since its inception, endoscopy has evolved from a solely diagnostic procedure to an expanding therap...
A clinically comparable Convolutional Neural Network framework-based technique for performing automa...
OBJECTIVES: Diagnosis of inflammatory bowel diseases (IBD) involves combining clinical, laboratory, ...
PURPOSE: Pancreatic cystic neoplasms (PCNs) are relatively rare neoplasms and difficult to be classi...
Ultrasound imaging is a commonly used technology for visualising patient anatomy in real-time during...
BACKGROUND: Diagnosis of early gastric cancer (EGC) under narrow band imaging endoscopy (NBI) is dep...
Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate ...
Colon cancer is a disease characterized by the unusual and uncontrolled development of cells that ar...
Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the...
BACKGROUND: The camera of an endoscope is fixed to the device, and the image rotates together with t...
A system for predicting apparent bidirectional permeability (P) across Caco-2 cells of diverse chemi...
Every year, nearly two million people die as a result of gastrointestinal (GI) disorders. Lower gast...
OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains chal...
AIM: The aim was to describe the robot-assisted intracorporeal anastomosis technique in left colon s...
This study aimed to explore the value of abdominal computerized tomography (CT) three-dimensional re...
OBJECTIVES: The aim of the study was to implement a non-invasive model to predict ascites grades amo...
Computer tomography texture analysis (CTTA) based on the V-Net convolutional neural network (CNN) al...
We aimed to explore novel biomarkers involved in alterations of metabolism and gene expression relat...
OBJECTIVES: To propose deep-learning (DL)-based predictive model for pathological complete response ...