Evaluation and Optimization of Machine Learning Algorithms for Individual Bladder Filling Level Prediction by a Sensor System
Evaluation and Optimization of Machine Learning Algorithms for Individual Bladder Filling Level Prediction by a Sensor System
The aim of this study is to evaluate the bladder filling level of the study participants using the inContAlert sensor. The generated data will be used for the evaluation and optimization of the machine learning algorithms to be able to make precise predictions about the individual bladder fill level.
In particular, the hypothesis that the bladder filling level can be estimated by the algorithm will be tested. When testing the hypothesis, it should be determined which deviation (measured by the mean absolute percentage error) of the estimation/prediction differs from the actual value (obtained by measuring the urine output using a measuring cup in combination with kitchen scales).
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