Thomas WJ Ash1, Guy B. Williams1, Fiona Regan2, Sally Georgia Harding1, Tero Saukkonen2, David B. Dunger2, T Adrian Carpenter1, Alison Sleigh1
1Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, Cambridgeshire, United Kingdom; 2Department of Paediatrics, University of Cambridge, Cambridge, Cambridgeshire, United Kingdom
Using machine learning (support vector machines) we construct a model that classifies soleus muscle spectra of adolescents into Type 1 diabetes / control groups with 95% accuracy in leave one out tests. This is an improvement on previous analysis of the data using solely IMCL peak area calculations which achieves 84% accuracy. The model confirms that IMCL height increases in type one diabetics, as well as showing that creatine and choline peaks are broadened in the type 1 diabetic group.