University of Groningen

machine learning learning vector quantization supervised learning relevance learning tumor classification neural networks statistical physics of learning prototype-based systems interpretable machine learning explainable ai adrenal tumors phase transitions self-organizing maps biomedical data unsupervised learning artificial intelligence adrenal tumours endocrinology steroid metabolomics classification learning curves metric learning neurodegenerative disease gmlvq feature selection layered neural networks tissue-specific ribosome disordered systems regression cytokine expression activation functions hidden units t-sne bioinformatics distance based classifiers parkinson fdg-pet gene expression data cancer classfication steroids hormones aldosteronism primary aldosteronism relevance matrix tumour classification metabolomics xai translational medicine multi-source data ssm/pca lvq transfer learning rheumatoid athritis life science data hidden unit specialization learning of a rule learning from examples data science learning theory statistical mechanics statistical physics ribosome composition pca selforganizing map ribosomal proteins ribosome annealed approximation deep learning feedforward networks prototype-ba learning vector quantizaation medical data pet scan brain images rheumatoid arthritis adaptive distance measures relu sigmoidal u-map ribosomae proteins mrna gene expression life-sciences prototype based systems student teacher model species translation proteomics systems biology brain-inspired computing prototype based systesm neuroimaging brain scan data risk prediction galaxy classification astroinformatics biomarker