Using Bayesian Neural Networks and multi-task learning to predict the clinical disease markers of MS patients and form a recommendation regarding the possible therapy switches.

Additional Metadata
Keywords	Bayesian Neural Networks; Multi-task learning; multiple sclerosis; medical decision making
Thesis Advisor	Sun, Y., Paap, R.
Persistent URL	hdl.handle.net/2105/56947
Series	Econometrie
Organisation	Erasmus School of Economics
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Schepper, M. de. (2021, February 26). Using Bayesian Neural Networks and multi-task learning to predict the clinical disease markers of MS patients and form a recommendation regarding the possible therapy switches.. Econometrie. Retrieved from http://hdl.handle.net/2105/56947

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