This prize recognizes the excellence of emerging health services and policy researchers at the early career stage.

The annual report highlights Drs. Laura Sikstrom and Marta Maslej’s work in using machine learning to design equitable care delivery (p. 26).

CAMH Foundation’s new Research Report highlights Drs. Laura Sikstrom and Marta Maslej’s work in using machine learning to design equitable care delivery (p.18).

In the episode, “The Compassion Code, Promoting Fairness in AI for Mental Health,” Laura Sikstrom and Sean Hill discuss the meaning of fairness in mental health and the concepts used to support it. Aired January 2024.

Marta Maslej, Project Scientist at the Centre for Addiction and Mental Health announced as a Fellow for: Promoting compassionate care in acute psychiatry with human-AI teams

Co-created with developers of the FairLearn Python package, Yifan Wang, Marta Maslej and Laura Sikstrom published a tutorial demonstrating how to carry out a bias assessment of a Machine Learning model in mental health.

Congratulations to our summer student, Valeria Khudiakova!

‘Conceptualising fairness: three pillars or medical algorithms and health equity’ announced as a BMJHCI Top 10 Most Downloaded paper of 2022!

Laura Sikstrom, Project Scientist at the Centre for Addiction and Mental Health announced as a Fellow for: Co-designing a Fairness Dashboard for clinical applications of Artificial Intelligence in mental health

‘Conceptualising fairness: three pillars for medical algorithms and health equity’ selected as May’s Editor’s Choice.

Laura Sikstrom, University of Toronto, Sean Hill, University of Toronto awarded for: A Computational Ethnographic Approach to Building Fair Models of Inpatient Violence in Emergency Psychiatry

CAMH-KCNI team win seed funding for: Building Fair Machine Learning Models: Using Big Data to Explore Inequities in Risk Assessment at the Centre for Addiction and Mental Health