Our hypothesis was that conducting proteomic analysis on clinical laboratory samples which are intended for the fecal calprotectin test would enable the develop-ment of a highly sensitive and specific non-invasive stool test based on mass spec-trometry. To investigate this hypothesis, we combined and applied our expertise in basic research, clinical practice, and bioinformatics to develop a precise ma-chine-learning model for the accurate diagnosis of active IBD from symptomatic non-IBDpatients.