Published Research

Canadian Medical Association Journal – Implementing machine learning in medicine

Machine learning has the potential to transform health care, although its current application to routine clinical practice has been limited.

Multidisciplinary partnership between technical experts and end-users, including clinicians, administrators, and patients and their families, is essential to developing and implementing machine-learned solutions in health care.

A 3-phase framework can be used to describe the development and adoption of machine-learned solutions: an exploration phase to understand the problem being addressed and the deployment environment, a solution design phase for the development of machine-learned models and user-friendly tools, and an implementation and evaluation phase to deploy and assess the impact of the machine-learned solution.