AIMC Topic: Crohn Disease
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Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases.
BMC microbiology
Jun 6, 2025
Gut microbiota has been implicated in the pathogenesis of multiple gastrointestinal (GI) and systemic metabolic and inflammatory disorders where disrupted gut microbiota composition and function (dysbiosis) has been found in multiple studies. Thus, h...
Deep learning reconstruction for T2-weighted and contrast-enhanced T1-weighted magnetic resonance enterography imaging in patients with Crohn's disease: Assessment of image quality and clinical utility.
Clinical imaging
May 30, 2025
PURPOSE: To investigate the image quality of deep learning-reconstructed T2-weighted half-Fourier single-shot turbo spin echo (DL T2 HASTE) and contrast-enhanced T1-weighted volumetric interpolated breath-hold examination (DL T1 VIBE) of magnetic res...
Ge-SAND: an explainable deep learning-driven framework for disease risk prediction by uncovering complex genetic interactions in parallel.
BMC genomics
May 1, 2025
BACKGROUND: Accurate genetic risk prediction and understanding the mechanisms underlying complex diseases are essential for effective intervention and precision medicine. However, current methods often struggle to capture the intricate and subtle gen...
Identification of Crohn's Disease-Related Biomarkers and Pan-Cancer Analysis Based on Machine Learning.
Mediators of inflammation
Apr 4, 2025
: In recent years, the incidence of Crohn's disease (CD) has shown a significant global increase, with numerous studies demonstrating its correlation with various cancers. This study aims to identify novel biomarkers for diagnosing CD and explore the...
Deep representation learning for clustering longitudinal survival data from electronic health records.
Nature communications
Mar 14, 2025
Precision medicine requires accurate identification of clinically relevant patient subgroups. Electronic health records provide major opportunities for leveraging machine learning approaches to uncover novel patient subgroups. However, many existing ...
Machine learning for temporary stoma after intestinal resection in surgical decision-making of Crohn's disease.
BMC gastroenterology
Feb 25, 2025
BACKGROUND: Crohn's disease (CD) often necessitates surgical intervention, with temporary stoma creation after intestinal resection (IR) being a crucial decision. This study aimed to construct novel models based on machine learning (ML) to predict te...
Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn's disease by bioinformatics analysis and machine learning.
Scientific reports
Jan 27, 2025
Crohn's disease (CD) is a chronic inflammatory bowel disease with an unknown etiology. Ubiquitination plays a significant role in the pathogenesis of CD. This study aimed to explore the functional roles of ubiquitination-related genes in CD. Differen...
Development of Time-Aggregated Machine Learning Model for Relapse Prediction in Pediatric Crohn's Disease.
Clinical and translational gastroenterology
Jan 1, 2025
INTRODUCTION: Pediatric Crohn's disease (CD) easily progresses to an active disease compared with adult CD, making it important to predict and minimize CD relapses. However, prediction of relapse at various time points (TPs) during pediatric CD remai...
Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.
Scientific reports
Dec 30, 2024
Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as one of the most prevalent malignant tumors of the digestive tract, has been indicated by research to have a close association with CD. This study empl...
Deep Learning-Enabled Rapid Metabolic Decoding of Small Extracellular Vesicles via Dual-Use Mass Spectroscopy Chip Array.
Analytical chemistry
Dec 23, 2024
The increasing focus of small extracellular vesicles (sEVs) in liquid biopsy has created a significant demand for streamlined improvements in sEV isolation methods, efficient collection of high-quality sEV data, and powerful rapid analysis of large d...
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