Prediction and prevention of sexual dysfunction using a machine learning approach

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.

Effectiveness of EarlyDetect, a psychiatric assessment program, using a mobile APP interface - Phase 2

Mental health illness cost over $50 billion in the Canadian economy annually, and is prevalent at workplace. The cost and prevalence of menial health illness can be greatly mitigated with early detection and intervention. EarlyDetect is a program developed by Chokka Center for Integrative Health for convenient, accurate and reliable self-assessment of mental illness, and has been validated in a pen-and-paper form.

Effectiveness of EarlyDetect, a psychiatric assessment program, using a mobile APP interface

Mental health illness cost over $50 billion in the Canadian economy annually, and is prevalent at workplace. The cost and prevalence of menial health illness can be greatly mitigated with early detection and intervention. EarlyDetect is a program developed by Chokka Center for Integrative Health for convenient, accurate and reliable self-assessment of mental illness, and has been validated in a pen-and-paper form.