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Bayesian methods for time series classification

The analysis of protein concentrations in liquids plays an important role in medical diagnostics. We combine Bayesian methods and artificial neural networks for real-time predictions of the concentrations based on observations of the corresponding chemical reactions. Our prototype model for classification of different protein concentrations reduces the prediction time by 90%. Now we are in the process of generalizing our technique for regression.

Principle Investigators: Pavel GurevichHannes Stuke
Members: Julian Stastny