QPSi Academy launches second course in AI in medicine curriculum series
AI-Based Medicine Technical Expertise available now for enrollment
Nov. 1, 2023 — The UF College of Medicine’s AI in medicine curriculum, now housed under the Quality and Patient Safety initiative, or QPSi, provides courses that teach UF and non-UF medical professionals, faculty and students how to use AI in the clinical setting. The curriculum demonstrates how through AI, health care providers can use synthesized data and models to make the best clinical decisions possible and plans of action to enhance care quality and safety of patients.
Falling under the education pillar of the College of Medicine’s strategic plan and in collaboration with the College of Education, this first-of-its-kind curriculum will contain several courses, the second of which launched this fall. As part of the QPSi Academy, these courses provide a high-level overview of AI theory and application in the form of bite-sized video lessons that are easily digested by busy health care providers, covering topics such as what is AI, how can it be used in medicine and how to converse and collaborate with other medical and experts specializing in AI and machine learning.
“The advantage of presenting AI applied to medicine to physicians is that they are in a unique position to incorporate AI tools that they build directly into clinical practice,” said François Modave, Ph.D., the assistant dean of the QPSi Academy, Training and Fellowship Programs.
Modave developed the courses alongside Chris Giordano, M.D., a professor of anesthesiology; and Patrick Tighe, M.D., M.S., the executive director of QPSi and associate dean for AI application and innovation.
As an introduction to the course series, the team created a simple one-hour primer to give learners an understanding of AI fundamentals and terminology, as well as its applications in medicine. The primer includes interviews from expert UF faculty members who discuss their experience using AI in the clinical setting and their predictions for its use in the future. Following the introduction is the first course, titled “Foundations of AI-Based Medicine,” where participants develop the fundamentals of AI in health care, learn vocabulary and prepare for the next two courses offered in the curriculum.
“By creating a strong working knowledge of AI among our clinicians, I think UF could leverage this tool to improve health care delivery while increasing scientific discovery,” Giordano said. “This means all of our students, residents and faculty will have to become conversant in AI so we can create this culture of AI proficiency.”
The second course, “AI-Based Medicine Technical Expertise,” was released in September and focuses on the foundations of programming and coding in the Python language and how they can be used in AI for practitioners to develop models relevant to their research or clinical duties.
This course also serves as a segue into the third course in the series, “An Introduction to Deep Learning in Medicine.” Currently being finalized, this unit focuses on the core ideas of deep learning and other advanced AI methodologies primarily applied to image analysis, such as computer vision for medical imaging.
In outlining the long-term impact the curriculum aims to have, Tighe said, “I think we’ll know we’ve been successful when physicians are asking different kinds of questions surrounding evidence-based medicine — questions that are more fully able to leverage the incredible creativity made possible by state-of-the-art AI algorithms.”
Interested in taking the AI in medicine courses?
Each course can be taken for continuing medical education, or CME, credit. UF faculty, staff and students can use discount codes to take the non-CME courses free of charge or the CME courses with a $25 discount. Non-UF medical professionals, faculty and students can enroll in CME or non-CME versions of the courses for a fee.
Participants looking to earn UF’s distance learning AI certificate can use the CME version of the courses to count toward that certification.