Determining gastrointestinal tract dysbiosis using machine learning techniques

2015

Masteroppgave informasjons- og kommunikasjonsteknologi - Universitetet i Agder, 2015 This thesis explores machine learning techniques for the purpose of determining gastrointestinal tract dysbiosis. Dysbiosis is an unbalance of bacteria flora. Stool sample analysis of relevant bacterias can be used in "diagnosis" of this condition. The problem is how to best classify dysbiosis from a healthy balance of bacteria. Pattern recognition methods could be used to create a diagnostic decision support system. The approach includes comparisons between classifiers with the additional use of feature reduction techniques. Experiments show that the accuracy varies significantly depending of which classif…