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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.
Bo Cao
Yang Liu
Chokka Center for Integrative Health
Education
Medical devices
Accelerate
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