Sexual dysfunction is pervasive in our society and is associated with a blend of biological, psychological, relational and contextual risk factors. In this project we will apply machine learning algorithms on a set of known risk factors of sexual dysfunction to predict whether a new patient suffers from sexual dysfunction and whether sexual dysfunction will improve based on specific patient treatment plans. This research work will set the foundation on building a artificial intelligent powered sexual dysfunction module of EarlyDetect, a psychiatric screening tool developed by Chokka Center for Integrative Health aimed to enhance accuracy and efficiency of the mental health screening process in Canada.
Chokka Center for Integrative Health
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