Dalla Lana School of Public Health

Links

• Register: https://www.eventbrite.ca/e/ai-evidence-and-ethics-a-pathway-for-clinical-translation-registration-127384782313

JCB Bioethics Seminar Series 2020-21

Speakers:

Melissa McCradden, PhD, MHSc, Bioethicist, The Hospital for Sick Children, Assistant Professor, Dalla Lana School of Public Health, University of Toronto

James Anderson, PhD, MHA, MA, Bioethicist, The Hospital for Sick Children, Assistant Professor, Institute for Health Policy, Management and Evaluation, University of Toronto

Elizabeth Stephenson, MD, MSc, Professor, Department of Paediatrics, University of Toronto, Section Head of Cardiac Electrophysiology, The Hospital for Sick Children

About this Seminar:

Healthcare artificial intelligence (AI) is increasingly viewed as technological intervention with immense potential to enhance patient outcomes by enabling anticipation, preparation, and ideally prevention of harms. But the promise held by any novel intervention must be proven empirically in the interest of responsible and ethical adoption of beneficial tools. Precisely how to demonstrate the benefit of machine learning (ML)-based tools is a topic of intense debate.

In this presentation, we will defend our view that the process of developing healthcare ML is most appropriately evaluated through a research pathway by exploring the ethical grounding of both research and the competing framework of quality improvement.

We will describe our three-phase ML pipeline grounded in research ethics for the validation, evaluation, and translation of clinical ML tools which was implemented recently at The Hospital for Sick Children. The pipeline consists of: Phase 1) data access protocols and governance to enable exploratory ML; Phase 2) Development and conduct of prospective, non-interventional (silent trial) protocols to demonstrate feasibility and provisional efficacy data; and Phase 3) the development and conduct of clinical trials to validate the efficacy of the model with respect to defined clinical endpoints/outcomes.

Grounding ML development and implementation in the research ethics pathway achieves two crucial goals: a pathway for progress in clinical ML becomes readily available; and trust in clinical ML is fostered by maintaining alignment with established legal and ethical standards for clinical research.

Additional Details:

This event is free and is open to the general public. The direct link to the seminar will be sent out to registered participants before the event. All of the JCB Bioethics Seminar are now being live streamed to our YouTube channel. Subscribe to receive notices of live events.

Questions? Please email Laurie Bulchak, laurie.bulchak@utoronto.ca.