Illustrations of how T-DPSOM can be used to cluster patients into different sub-phenotypes and potentially gain better understanding of disease patterns and ...

Apr 8, 2021 · We demonstrate that T-DPSOM provides interpretable visualizations of patient state trajectories and uncertainty estimation.

T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States. Reference. Laura Manduchi, Matthias Hüser, Martin Faltys ...

T-DPSOM: An interpretable clustering method for unsupervised learning of patient health states. Laura Manduchi, Matthias Hüser, Martin Faltys, Julia Vogt ...

Apr 10, 2021 · Illustrations of how T-DPSOM can be used to cluster patients into different sub-phenotypes and potentially gain better understanding of disease ...

T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states · No full-text available · Citations (8) · References (32).

T-DPSOM can be used cluster patients into different sub-phenotypes and can gain better insights for disease patterns and individual patient health state. For ...

T-dpsom: An interpretable clustering method for unsupervised learning of patient health states. L Manduchi, M Hüser, M Faltys, J Vogt, G Rätsch, V Fortuin.

Oct 3, 2019 · We show that DPSOM achieves superior clustering performance compared to current deep clustering methods on MNIST/Fashion-MNIST, while maintaining the ...

ML4H Workshop, NeurIPS 2020. [paper][code]; T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states. Laura Manduchi ...