Q&A with Leo Thompson
Leo Thompson is a medical student in the Feinberg School of Medicine.
How did you first hear about the Institute for Augmented Intelligence in Medicine?
I heard about I.AIM from a lecture by Dr. David Liebovitz, who frequently leads informative sessions with the medical students about how we can use different data science tools with clinical and research applications. I was intrigued by the concept of a "health data gymnasium" where data available for machine learning analysis could be stored and made available to students.
What factors interested you to work with I.AIM?
I have always been intrigued by the intersection of healthcare and technology, and therefore I.AIM seemed like the perfect team with whom to collaborate. The institute is also run by a very supportive group of staff and clinicians. The availability of clinical data for analysis was another factor that is unique to I.AIM that makes collaboration easy and streamlined.
How has your experience in I.AIM changed you?
I.AIM has helped me learn to use practical machine learning tools to help answer important medical questions. I.AIM has also helped me learn to better craft these clinical questions for further machine learning analysis. It has also taught me new frameworks of how to approach big data in healthcare, and the important insights that can be made using machine learning tools.
Would you like to share a specific project you're proud of?
I am very thankful for I.AIM's support, and especially that of Dr. Beatrice Nardone! Dr. Nardone and I worked together to use clustering analysis on patients with metastatic melanoma, and as a result, were able to make some clinical insights. You can read more about our research here.
What has been your greatest challenge?
Balancing medical school and research is not easy! But I.AIM has been very supportive both by providing resources and guidance, and making the process as simple as it can be.