Emerging use of artificial intelligence in inflammatory bowel disease |
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Authors: | Arushi Kohli Erik A Holzwanger Alexander N Levy |
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Affiliation: | Arushi Kohli, Department of Internal Medicine, Tufts Medical Center, Boston, MA 02111, United StatesErik A Holzwanger, Alexander N Levy, Division of Gastroenterology and Hepatology, Tufts Medical Center, Boston, MA 02111, United States |
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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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Keywords: | Artificial intelligence Machine learning Automated diagnostics Colorectal neoplasia screening Multiomic data Predictive models |
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