Individual risk profiles and prediction of the clinical course of affective disorders
Affective disorders such as depression are among the most common psychiatric disorders and represent one of the leading causes of disability worldwide. In treating depression, we are currently unable to estimate how successful any one course of action will be at alleviating symptoms for each individual patient. Therefore, our goal is to gather information at the beginning and during inpatient treatment – through systematic collection and analyses of data from electronical health records as well as from scientific studies – in order to create individual risk profiles and predict the individual disease course. Specifically, the project SEED 11/18 aims to develop models that would aid in identifying patients at risk of recurring depressive episodes. A subsequent research aim is the translation of our findings into improved preventive, diagnostic, and therapeutic interventions in the clinical field. To achieve this aim SEED 11/18 was designed as a collaborative project of the Institute of Medical Informatics and the Department of Psychiatry and Psychotherapy thus bringing together both clinical expertise and techniques as well as in-depth knowledge in the domain of data science and digitalized medicine.
Contact: Dr. Nils Opel
Project number: SEED 11 / 18