Software model predicts risk of depression relapse

Posted on October 24, 2014

German neuroscientists have written a software program that they believe can calculate the risk for experiencing a major depression relapse.

For the project, Selver Demic, M.D., of the Ruhr University Bochum and his colleagues from the Mercator Research Group examined a variety of factors that influence depression.

The model includes factors such as rate of memory lapses, cognitive bias, and activity levels of the mood-related neurochemical serotonin. Some of the variables such as serotonin are well-recognized as being associated with depression while other items include social factors such as family demographics and job situation. A unique aspect of the research is the inclusion of all factors into one model.

After using the model for analysis, Demic discovered the observed patterns of depression could only be explained by a division into two distinct patient groups: A high-risk group whose parameters are so unfortunately aligned that they will always suffer from recurring depressions; another group in which depression will only occur by chance.

The scientists also wanted to compile a systematic definition for the individual disease states based on objective facts, moving beyond the existing classification system that has some degree of subjectivity. When assessing which phase the patient is currently undergoing, psychologists and doctors will also always rely on their intuition and experience.

Consequently, the neuroscientist developed a mathematical model, a so-called finite state machine (FSM). This tool is fed data regarding a patient’s state every day. Based on those data and as result of the time course, the FSM calculates the disease state that the patient is currently undergoing.

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Source material from Psych Central


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