Course Description

Artificial intelligence (AI) is increasingly impacting many research and clinical aspects of biomedicine, and the use of AI in medicine is anticipated to grow in many ways. This course is intended for current and future clinicians. We intentionally define “clinicians” broadly so as to refer to anyone working with patients/research subjects in a clinically-oriented way, whether at the bedside, in the lab, or behind a computer. The overarching goal of the course is to familiarize participants in the methods and uses of AI in biomedicine. This will be an asynchronous, self-paced course that will include short video presentations, readings from a variety of sources (including medical and nonmedical articles) assessments and assignments. To stay current, additional or optional course material may be changed or added during the course. Absolutely no coding, computer science, or AI experience is required or expected other than general interest in the field.

Learner Outcomes

When you complete the course successfully, you will be able to:

• Understand the basic themes and principles related to diverse AI methods utilized in biomedicine, including related to the ability to analyze different important data types.
• Evaluate past and current real-world case studies and current applications of AI in clinical and research biomedical sphere, examining their effectiveness, limitations, and impact on healthcare outcomes.
• Identify and critically assess key challenges and opportunities associated with the integration of AI technologies in biomedicine, considering factors such as privacy, bias, regulatory aspects, and the potential for innovation in medical research and clinical practice.

Microcredential(s) 

This course applies toward the AI in Medicine digital badge.

Textbook Information

There is no textbook for purchase required for this course.