PhD Defense: Psychosis Prognosis Prediction integrating human perspectives and artificial intelligence
PhD Defense of Violet van Dee
Towards better predictions in psychosis: the power of experience, expertise and machine learning
How can we better predict how people with a psychotic disorder will recover? This dissertation explores this question from three perspectives: the views of those involved, the predictors of recovery, and the use of machine learning techniques in mental health care.
We examined whether patients, relatives and professionals agree on what 'recovery' means. This was not always the case. Professionals often focus on reducing symptoms, while patients and relatives consider other aspects just as important, such as having a meaningful daily routine, social connections and a sense of purpose. For good collaboration, it is important to recognise and respect these different views.
Next, we looked at which factors best predict recovery. The level of functioning at the start of the illness turned out to be the strongest predictor for future outcomes. This shows how important it is to identify and address problems early鈥攖hrough quick access to care, lifestyle support and preventing school dropout.
- Start date and time
- End date and time
- Location
- PhD candidate
- Violet van Dee
- Dissertation
- Psychosis Prognosis Prediction integrating human perspectives and artificial intelligence
- PhD supervisor(s)
- prof. dr. W. Cahn
- Co-supervisor(s)
- dr. H.G. Schnack
- dr. W. Swildens