Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders. - Sreejita Ghosh; Elizabeth Sarah Baranowski; Rick van Veen; Gert-Jan de Vries; Michael Biehl; Wiebke Arlt; Peter Tiño; Kerstin Bunte (ESANN, 2017)

Wearable accelerometer based extended sleep position recognition. - Sarah Fallmann; Rick van Veen; Liming Chen 001; David Walker 014; Feng Chen 004; Chengsheng Pan (Healthcom, 2017)

Machine Learning Based Analysis of FDG-PET Image Data for the Diagnosis of Neurodegenerative Diseases. - Rick van Veen; Lidia Talavera-Martínez; Rosalie V. Kogan; Sanne K. Meles; Deborah Mudali; Jos B. T. M. Roerdink; Federico Massa; M. Grazzini; Jose A. Obeso; Maria C. Rodriguez-Oroz; Klaus Leonard Leenders; Remco J. Renken; et al. (APPIS, 2018)

An application of generalized matrix learning vector quantization in neuroimaging. - Rick van Veen; Vita Gurvits; Rosalie V. Kogan; Sanne K. Meles; Gert-Jan de Vries; Remco J. Renken; Maria C. Rodriguez-Oroz; Rafael Rodriguez-Rojas; Dario Arnaldi; Stefano Raffa; Bauke M. de Jong; Klaus Leonard Leenders; et al. (Comput. Methods Programs Biomed., 2020)

sklvq: Scikit Learning Vector Quantization. - Rick van Veen; Michael Biehl; Gert-Jan de Vries (J. Mach. Learn. Res., 2021)

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder. - Rick van Veen; Sanne K. Meles; Remco J. Renken; Fransje E. Reesink; Wolfgang H. Oertel; Annette Janzen; Gert-Jan de Vries; Klaus Leonard Leenders; Michael Biehl (Comput. Methods Programs Biomed., 2022)

Subspace corrected relevance learning with application in neuroimaging. - Rick van Veen; Neha Rajendra Bari Tamboli; Sofie Lövdal; Sanne K. Meles; Remco J. Renken; Gert-Jan de Vries; Dario Arnaldi; Silvia Morbelli; Pedro Clavero; José A. Obeso; Maria C. Rodriguez-Oroz; Klaus Leonard Leenders; et al. (Artif. Intell. Medicine, 2024)