Detection of Mental Health Conditions from Textual Device Communication

Research into child safety applications using Artificial Intelligence (AI) methods is a new area of investigation. SafeToNet is continuing to develop AI monitoring tools together with a team of researchers at the University of Ottawa. These tools, when used over time, will take advantage of outgoing text-based communications from devices to detect the early onset and progression of developmental and mental health issues in youth. The addition of a postdoctoral researcher in Natural Language Processing (NLP) will allow the project to run quality assessments of the text-based data sets that we are developing for the purposes of assessing these behavioural and mental health concerns in youth. This will allow SafeToNet to develop new deep-learning tools and assess their performance against current research in NLP. The technology will be used in real time detection of safety and childhood development issues, with the technology being immediately deployed in the monitoring tool.

Faculty Supervisor:

Diana Inkpen

Student:

Stefania Pecòre

Partner:

SafeToNet Canada Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Ottawa