KEY POINTS
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.