Print Email Facebook Twitter Finding Biomarkers for Type 2 Diabetes Title Finding Biomarkers for Type 2 Diabetes Author Das, Aratrika (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Pattern Recognition and Bioinformatics) Contributor Abeel, T.E.P.M.F. (mentor) van der Toorn, E.A. (mentor) Calderon Franco, D. (mentor) Höllt, T. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2023-06-29 Abstract Type 2 Diabetes is a very prevalent disease in current times and leads to significant adverse effects. Recently, there has been a growing interest in the association of the human gut microbiome with respect to chronic diseases like Type 2 Diabetes with the aim to identify biomarkers. In this study, we researched the effect of different machine learning and feature selection techniques to identify biomarkers for Type 2 Diabetes that can later be used for diagnosis and prediction. The main methods that we explored were Random Forests,Linear Regression, Support Vector Machines andXGBoost along with mRMR and CMIM as feature selection techniques. These methods were applied to data taken from Europe and China. We found that mRMR improved the performance of the Random Forest classifier compared to CMIM.Apart from finding biomarkers specific to one location, we found that Clostridiales, Clostridium, Roseburia and Lactobacillus could be of interestin the prediction of Type 2 Diabetes irrespective of location. This study verified biomarkers found in previous literature and evaluated several techniquesfor the prediction of the disease across different regions. Subject BioinformaticsType 2 diabetesMachine learning To reference this document use: http://resolver.tudelft.nl/uuid:c626e4c7-29c9-4dbb-8cb3-8c3d704df81f Part of collection Student theses Document type bachelor thesis Rights © 2023 Aratrika Das Files PDF CSE3000_Final_Paper.pdf 837.06 KB Close viewer /islandora/object/uuid:c626e4c7-29c9-4dbb-8cb3-8c3d704df81f/datastream/OBJ/view