Machine learning and metabolomics identify biomarkers associated with the disease extent of ulcerative colitis

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Ulcerative colitis (UC) is a chronic inflammatory disease characterized by recurrent diarrhea and abdominal pain.
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Machine learning algorithms identified 8 key metabolites that distinguish patients with UC from healthy controls.
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The study confirmed 220 differential metabolites between UC patients and healthy individuals using OPLS-DA analysis.
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The random forest model achieved a prediction accuracy of 100% across all training sets for UC severity.
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Metabolomic profiling revealed significant differences in serum metabolite levels associated with varying extents of UC.

Journal Of Crohn's And Colitis

by Changchang Ge, Yi Lu, Zhaofeng Shen, Yizhou Lu, Xiaojuan Liu, Mengyuan Zhang, Yijing Liu, Hong Shen, Lei Zhu
February 4, 2025

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