AIMC Topic: Crohn Disease
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Novel Transcriptomic Signatures in Fibrostenotic Crohn's Disease: Dysregulated Pathways, Promising Biomarkers, and Putative Therapeutic Targets.
Inflammatory bowel diseases
Jun 13, 2025
BACKGROUND: Fibrosis is a common complication in Crohn's disease (CD), often leading to intestinal strictures. This study aims to explore the transcriptomic signature of fibrostenotic ileal CD for a comprehensive characterization of biological and ce...
Prediction of endoscopic restenosis after endoscopic balloon dilation in patients with Crohn's disease: a machine learning approach.
Surgical endoscopy
Jun 1, 2025
BACKGROUND: Endoscopic balloon dilation (EBD) is recognized as a minimally invasive and effective procedure for managing intestinal stenosis in patients with Crohn's disease (CD). It offers an alternative to surgery and has been shown to improve the ...
Developing a Machine-Learning Prediction Model for Infliximab Response in Crohn's Disease: Integrating Clinical Characteristics and Longitudinal Laboratory Trends.
Inflammatory bowel diseases
May 12, 2025
BACKGROUND: Achieving long-term clinical remission in Crohn's disease (CD) with antitumor necrosis factor α (anti-TNF-α) agents remains challenging.
Identification and validation of shared biomarkers and drug repurposing in psoriasis and Crohn's disease: integrating bioinformatics, machine learning, and experimental approaches.
Frontiers in immunology
Jan 1, 2025
BACKGROUND: Psoriasis and Crohn's disease (CD) are chronic inflammatory diseases that involve complex immune-mediated mechanisms. Despite clinical overlap and shared genetic predispositions, the molecular pathways connecting these diseases remain inc...
Automatic Segmentation and Radiomics for Identification and Activity Assessment of CTE Lesions in Crohn's Disease.
Inflammatory bowel diseases
Nov 4, 2024
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...
Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.
World journal of gastroenterology
Jul 7, 2024
BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease (CD) is a challenge in clinical practice.
Identification of Ulcers and Erosions by the Novel Pillcam™ Crohn's Capsule Using a Convolutional Neural Network: A Multicentre Pilot Study.
Journal of Crohn's & colitis
Jan 28, 2022
BACKGROUND AND AIMS: Capsule endoscopy is a central element in the management of patients with suspected or known Crohn's disease. In 2017, PillCam™ Crohn's Capsule was introduced and demonstrated to have greater accuracy in the evaluation of extensi...
Deep learning conventional learning algorithms for clinical prediction in Crohn's disease: A proof-of-concept study.
World journal of gastroenterology
Oct 14, 2021
BACKGROUND: Traditional methods of developing predictive models in inflammatory bowel diseases (IBD) rely on using statistical regression approaches to deriving clinical scores such as the Crohn's disease (CD) activity index. However, traditional app...
The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.
Inflammatory bowel diseases
Jul 27, 2021
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...
Automated Detection of Crohn's Disease Intestinal Strictures on Capsule Endoscopy Images Using Deep Neural Networks.
Journal of Crohn's & colitis
May 4, 2021
BACKGROUND AND AIMS: Passable intestinal strictures are frequently detected on capsule endoscopy [CE]. Such strictures are a major component of inflammatory scores. Deep neural network technology for CE is emerging. However, the ability of deep neura...
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