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Updated: Nov 26, 2025

Fluorescence-mediated Tomography for the Detection and Quantification of Macrophage-related Murine Intestinal Inflammation
Published on: December 15, 2017
Emerging use of artificial intelligence in inflammatory bowel disease
Arushi Kohli1, Erik A Holzwanger2, Alexander N Levy3
1Department of Internal Medicine, Tufts Medical Center, Boston, MA 02111, United States.
Abstract:
Inflammatory bowel disease (IBD) is a complex, immune-mediated gastrointestinal disorder with ill-defined etiology, multifaceted diagnostic criteria, and unpredictable treatment response. Innovations in IBD diagnostics, including developments in genomic sequencing and molecular analytics, have generated tremendous interest in leveraging these large data platforms into clinically meaningful tools. Artificial intelligence, through machine learning facilitates the interpretation of large arrays of data, and may provide insight to improving IBD outcomes. While potential applications of machine learning models are vast, further research is needed to generate standardized models that can be adapted to target IBD populations.
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