Abstract
Mental illnesses are complex in etiology, dynamic over time, and to a large extent, influenced by the interaction between the individual patient and his or her environment. Big data deal with this complexity by using real-life data in real time from a real patient population. As such, big data provide opportunities to better understand the complexity and improve mental health care for patients at an individual level. The aim of this project was to explore the possibilities to develop decision support systems to predict the medication effects of antipsychotic drugs, antidepressants, and methylphenidate to reduce side effects and, hence, improve efficiency of treatment.
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