31 citations · 45 across the 8 of their papers we have counts for
8 papers
PlasmoFAB: A Benchmark to Foster Machine Learning for Plasmodium falciparum Protein Antigen Candidate Prediction
Jonas Christian Ditz, Jacqueline Wistuba-Hamprecht, Timo Maier +3
Motivation: Machine learning methods can be used to support scientific discovery in healthcare-related research fields. However, these methods can only be reliably used if they can…
Convolutional Motif Kernel Networks
Jonas C. Ditz, Bernhard Reuter, Nico Pfeifer
Artificial neural networks show promising performance in detecting correlations within data that are associated with specific outcomes. However, the black-box nature of such models…
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare
Ali Burak Ünal, Mete Akgün, Nico Pfeifer
To train sophisticated machine learning models one usually needs many training samples. Especially in healthcare settings these samples can be very expensive, meaning that one inst…
Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework
Efe Bozkir, Ali Burak Ünal, Mete Akgün +2
Eye tracking is handled as one of the key technologies for applications that assess and evaluate human attention, behavior, and biometrics, especially using gaze, pupillary, and bl…
An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes
Nora K. Speicher, Nico Pfeifer
Due to the complexity of cancer, clustering algorithms have been used to disentangle the observed heterogeneity and identify cancer subtypes that can be treated specifically. While…
Towards multiple kernel principal component analysis for integrative analysis of tumor samples
Nora K. Speicher, Nico Pfeifer
Personalized treatment of patients based on tissue-specific cancer subtypes has strongly increased the efficacy of the chosen therapies. Even though the amount of data measured for…
Partially blind domain adaptation for age prediction from DNA methylation data
Lisa Handl, Adrin Jalali, Michael Scherer +1
Over the last years, huge resources of biological and medical data have become available for research. This data offers great chances for machine learning applications in health ca…
Family-joining: A fast distance-based method for constructing generally labeled trees
Prabhav Kalaghatgi, Nico Pfeifer, Thomas Lengauer
The widely used model for evolutionary relationships is a bifurcating tree with all taxa/observations placed at the leaves. This is not appropriate if the taxa have been densely sa…