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Over ons Praktische zaken Waar vindt u ons M. (Michael) Biehl, Prof

Research interests

Machine Learning, Neural Networks, Data Analysis, Pattern Recognition, Biomedical Data, Bioinformatics, Classification, Supervised Learning, Unsupervised Learning, Computational Science, Scientific Computation, Modeling and Simulation, Statistical Physics

Publicaties

Hidden unit specialization in layered neural networks:: ReLU vs. sigmoidal activation

Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: A prospective test validation study

Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples

An application of generalized matrix learning vector quantization in neuroimaging

Supervised learning in the presence of concept drift: A modelling framework

Discriminative Subspace Emersion from learning feature relevances across different populations

Explainable machine learning for movement disorders - Classification of tremor and myoclonus

Interpretable machine learning for the diagnosis of hyperkinetic movement disorders

Interpretable modelling and visualization of biomedical data

IRMA: Machine learning-based harmonization of 18F-FDG PET brain scans in multi-center studies