Latest AI and machine learning research in inflammatory bowel disease for healthcare professionals.
Modeling human diseases as networks simplify complex multi-cellular processes, helps understand patterns in noisy data that humans cannot find, and thereby improves precision in prediction. Using Inflammatory Bowel Disease (IBD) as an example, here we outline an unbiased AI-assisted approach for target identification and validation. A network was built in which clusters of genes are connected by d...
BACKGROUND: We have developed the computer-aided detection (CADe) system using an original deep learning algorithm based on a convolutional neural network for assisting endoscopists in detecting colorectal lesions during colonoscopy. The aim of this study was to clarify whether adenoma miss rate (AMR) could be reduced with CADe assistance during screening and surveillance colonoscopy.
With the continuous improvement of human living standards, dietary habits are constantly changing, which brings various bowel problems. Among them, th...
We investigated the coupling phenomenon between plasmonic resonance and waveguide modes through theoretical and experimental parametric analyses on th...
DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attractive therapeutic target for obesity. Thus, devel...
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinica...
Colorectal cancer (CRC) is globally the third most common type of cancer. Colonoscopy is considered the gold standard in colorectal cancer screening a...
OBJECTIVE: Robotic endoscopes have the potential to dramatically improve endoscopy procedures, however current attempts remain limited due to mobility...
Colonoscopy is an effective tool for early screening of colorectal diseases. However, the application of colonoscopy in distinguishing different intes...
BACKGROUND: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment...
Precise determination and assessment of bladder cancer (BC) extent of muscle invasion involvement guides proper risk stratification and personalized t...
PURPOSE: A three-dimensional (3D) structure extraction technique viewed from a two-dimensional image is essential for the development of a computer-ai...
OBJECTIVES: This study review focuses on a deep learning method for the detection of colorectal lesions in colonoscopy and AI support for detecting co...
Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed netwo...
A colonoscopy is a medical examination used to check disease or abnormalities in the large intestine. If necessary, polyps or adenomas would be remove...
Despite the vast amount of metabolic information that can be captured in untargeted metabolomics, many biological applications are looking for a biolo...
Recurrent angina (RA) after percutaneous coronary intervention (PCI) has few known risk factors, hampering the identification of high-risk populations...
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interacti...
BACKGROUND: There are no established accurate models that use machine learning (ML) methods to preoperatively predict immediate remission after transs...