Latest AI and machine learning research in gastroenterology for healthcare professionals.
BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an...
BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but ...
BACKGROUND: The study aimed to construct an intelligent difficulty scoring and assistance system (DS...
The objective of the study is to compare the safety and efficacy of robot-assisted pancreaticoduoden...
Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prer...
Although there is no agreement on a definition of elderly, commonly an age cutoff of ≥ 65 or 75 year...
BACKGROUND: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance ...
Chronic liver disease (CLD) is currently one of the major causes of death worldwide. If not treated,...
Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory ...
BACKGROUND AND OBJECTIVE: Automatic functional region annotation of liver should be very useful for ...
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive...
Artificial intelligence (AI) has been attracting considerable attention as an important scientific t...
The nuclei segmentation of hematoxylin and eosin (H&E) stained histopathology images is an important...
STUDY OBJECTIVE: The Hominis surgical system is a novel robot-assisted system, designed specifically...
INTRODUCTION: The learning curve associated with robotic pancreatoduodenectomy (RPD) is a hurdle for...
IMPORTANCE: Machine-learning algorithms offer better predictive accuracy than traditional prognostic...
BACKGROUND: Society consensus guidelines are commonly used to guide management of pancreatic cystic ...
OBJECTIVES: Deep learning enables an automated liver and spleen volume measurements on CT. The purpo...
Artificial intelligence (AI), which has demonstrated outstanding achievements in image recognition, ...
In this paper, we propose and validate a deep learning framework that incorporates both multi-atlas ...
In this project, our goal is to develop a method for interpreting how a neural network makes layer-b...