1 citations · 1 across the 3 of their papers we have counts for
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Compositionality in Time Series: A Proof of Concept using Symbolic Dynamics and Compositional Data Augmentation
Michael Hagmann, Michael Staniek, Stefan Riezler
This work investigates whether time series of natural phenomena can be understood as being generated by sequences of latent states which are ordered in systematic and regular ways.…
Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series Forecasting
Michael Staniek, Marius Fracarolli, Michael Hagmann +1
Machine learning for early syndrome diagnosis aims to solve the intricate task of predicting a ground truth label that most often is the outcome (effect) of a medical consensus def…
Validity problems in clinical machine learning by indirect data labeling using consensus definitions
Michael Hagmann, Shigehiko Schamoni, Stefan Riezler
We demonstrate a validity problem of machine learning in the vital application area of disease diagnosis in medicine. It arises when target labels in training data are determined b…