  Faecal Calprotectin (FC) is a surrogate marker for intestinal inflammation,
termed Inflammatory Bowel Disease (IBD), but not for cancer. In this
retrospective study of 804 patients, an enhanced benchmark predictive model for
analyzing FC is developed, based on a novel state-of-the-art Echo State Network
(ESN), an advanced dynamic recurrent neural network which implements a
biologically plausible architecture, and a supervised learning mechanism. The
proposed machine learning driven predictive model is benchmarked against a
conventional logistic regression model, demonstrating statistically significant
performance improvements.
