Deep Learning to extract biomarkers for the diagnosis and personalized treatment of neuropsychiatric disorders

Psychological disorders have a major impact on people's lives. Rapid recovery depends on proper diagnosis and treatment. The problem is, however, that there are no objective criteria to determine exactly which psychiatric condition a patient has and which treatment is best for him or her.

In recent years, databases with thousands of brain scans have been created and computer power has increased enormously. This now makes it possible to investigate whether it is possible to objectify the diagnostics and to predict whether or not a patient benefits from a certain treatment. In order to do this, the right analysis techniques must first be developed. The aim of this research is to develop advanced techniques from artificial intelligence to analyse brain scans, and then to use these techniques for objective diagnostics and predicting the response to electroconvulsive therapy for patients with severe depression. This innovative research will yield new methods that enable tailor-made care in psychiatry and thus reduce the suffering pressure of patients and healthcare costs.


Project Updates

February 2020 - Q&A with dr. Guido van Wingen

More information
Titel project: Deep Learning to extract biomarkers for the diagnosis and personalized treatment of neuropsychiatric disorders

Programma: Commit2Data-Program

Organisatie: NWO

Looptijd: t/m 2022

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