AI Medical Compendium Journal:
Inflammatory bowel diseases

Showing 1 to 10 of 14 articles

Dietary Carrageenan Amplifies the Inflammatory Profile, but not Permeability, of Intestinal Epithelial Cells from Patients With Crohn's Disease.

Inflammatory bowel diseases
BACKGROUND: The consumption of ultra-processed foods has increased significantly worldwide and is associated with the rise in inflammatory bowel diseases. However, any causative factors and their underlying mechanisms are yet to be identified. This s...

Accurate, Robust, and Scalable Machine Abstraction of Mayo Endoscopic Subscores From Colonoscopy Reports.

Inflammatory bowel diseases
BACKGROUND: The Mayo endoscopic subscore (MES) is an important quantitative measure of disease activity in ulcerative colitis. Colonoscopy reports in routine clinical care usually characterize ulcerative colitis disease activity using free text descr...

AI-luminating Artificial Intelligence in Inflammatory Bowel Diseases: A Narrative Review on the Role of AI in Endoscopy, Histology, and Imaging for IBD.

Inflammatory bowel diseases
Endoscopy, histology, and cross-sectional imaging serve as fundamental pillars in the detection, monitoring, and prognostication of inflammatory bowel disease (IBD). However, interpretation of these studies often relies on subjective human judgment, ...

Automatic Segmentation and Radiomics for Identification and Activity Assessment of CTE Lesions in Crohn's Disease.

Inflammatory bowel diseases
BACKGROUND: The purpose of this article is to develop a deep learning automatic segmentation model for the segmentation of Crohn's disease (CD) lesions in computed tomography enterography (CTE) images. Additionally, the radiomics features extracted f...

Machine Learning-based Characterization of Longitudinal Health Care Utilization Among Patients With Inflammatory Bowel Diseases.

Inflammatory bowel diseases
BACKGROUND: Inflammatory bowel disease (IBD) is associated with increased health care utilization. Forecasting of high resource utilizers could improve resource allocation. In this study, we aimed to develop machine learning models (1) to cluster pat...

Improving the Computer-Aided Estimation of Ulcerative Colitis Severity According to Mayo Endoscopic Score by Using Regression-Based Deep Learning.

Inflammatory bowel diseases
BACKGROUND: Assessment of endoscopic activity in ulcerative colitis (UC) is important for treatment decisions and monitoring disease progress. However, substantial inter- and intraobserver variability in grading impairs the assessment. Our aim was to...

Utilizing Deep Learning to Analyze Whole Slide Images of Colonic Biopsies for Associations Between Eosinophil Density and Clinicopathologic Features in Active Ulcerative Colitis.

Inflammatory bowel diseases
BACKGROUND: Eosinophils have been implicated in the pathogenesis of ulcerative colitis and have been associated with disease course and therapeutic response. However, associations between eosinophil density, histologic activity, and clinical features...

The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.

Inflammatory bowel diseases
BACKGROUND: Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies may also provide prognostic opportunities. We evaluated machine learning models incorporating routi...

The Association Between Arthralgia and Vedolizumab Using Natural Language Processing.

Inflammatory bowel diseases
BACKGROUND: The gut-selective nature of vedolizumab has raised questions regarding increased joint pain or arthralgia with its use in inflammatory bowel disease (IBD) patients. As arthralgias are seldom coded and thus difficult to study, few studies ...