Integrating Genetics and Biometrics in Machine Learning for Enhanced Depression Diagnosis and Treatment Prediction

We are embarking on an exciting research project that aims to enhance how we diagnose and treat depression in young adults aged 18-29. Our team will use machine learning to better understand how a person’s genetic makeup and life experiences can affect their mental health. Specifically, we will enhance a tool called YMI, developed by our partner, nDatalyze. YMI already uses technology to predict mental health conditions, but we plan to make it even more accurate by including genetic information. The end goal is to make it easier and more accurate for healthcare professionals to diagnose depression and choose the best treatment options for each individual. For nDatalyze, this means their tool becomes more advanced and valuable, potentially leading to wider use in the healthcare field and helping more people get the right treatment for their mental health needs.

Faculty Supervisor:

Dale Dale Stevens

Student:

Partner:

nDatalyze Corp.

Discipline:

Computer science

Sector:

Information and cultural industries

University:

York University

Program: