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Detecting Multiple Sclerosis via breath analysis using an electronic Nose

Project summary

We will investigate whether an eNose can detect Multiple Sclerosis (MS) and monitor the disease’s progression. There is not yet a quick test nor a non-invasive method to identify patients with MS or distinguish between various types of MS. An electronic Nose is a diagnostic device to detect patterns in the compounds that are exhaled by patients. The disease-specific metabolic pathways give rise to specific compound-patterns in exhaled breath that aid in detecting diseases. Exhaled breath data and clinical parameters will be used to develop a predictive model to detect and monitor MS, based on supervised machine learning techniques

More detailed information

Principal Investigator:

Prof. dr. F.J.P.M. Huygen

Role Erasmus MC:




Project website:

Not available

Funding Agency: