Dr. Jethro Kwong: using machine learning to help patients with prostate cancer
Coming up on June 1, T-CAIREM will be hosting two public presentations by emerging University of Toronto researchers. Dr. Jethro Kwong is one of them. Kwong became a Medical Doctor in 2020 and is currently completing his residency. In his upcoming presentation he'll discuss how a machine learning model could provide more data to help urologists make better healthcare decisions for patients with prostate cancer. We caught up with him to learn more about his research interests.
What inspired you to pursue urology?
I was drawn to urology because it is a specialty that allows me to develop long-term relationships with my patients and positively impact their quality of life. Urologists manage a wide breadth of conditions from both a medical and surgical standpoint. As a tech enthusiast, urology is also one of the most technologically innovative surgical specialties – we regularly perform robotic-assisted surgeries and AI is booming in our specialty! I’m also incredibly grateful to my mentors who have been incredibly supportive of this project and inspired me to become a surgeon-scientist.
What inspired you to research this topic?
In clinical practice, we routinely use nomograms to predict overall risk of local cancer spread outside the prostate to help guide surgical strategy. However, these models are only based on a handful of predictors, even though we have a lot more data that is readily available. These models also do not predict side-specific risk of cancer spread (ie: has the cancer spread outside the prostate on the left-side, right-side, or both?). So, by combining the complete patient profile with machine learning, we feel that we can move beyond a one-size-fits-all model towards more personalized surgical planning.
What outcomes do you hope your research will eventually lead to?
We hope that this machine learning model will help set the new standard for more personalized surgical planning in prostate cancer surgery. Work is currently underway to further validate our model on diverse patient cohorts here in Canada and across the world!
What are your professional goals after you complete your studies at the U of T?
I aspire to be a surgeon-scientist, with a focus on developing AI applications in urology. Viewing problems through a clinical lens gives me the unique opportunity to identify areas that would most benefit from targeted AI interventions to improve patient care.
What do you like to do when you aren’t working?
Free time is quite limited as a resident! Whenever I can, I enjoy spending time with my family and catching up with my medical school friends. Prior to the pandemic, I loved playing squash!
What advice would you give to high school students who are interested in following in your footsteps?
Follow your passions! My path started with an interest in medicine and robotics back in high school, and I continued developing these interests in undergrad and medical school. Now, I’m training in a specialty where we regularly use a variety of technology (robots, lasers, and now AI) to help patients. There are many different paths to medicine, each with a unique way to teach you valuable soft skills to make you a better physician. Reach out to others pursuing the same path and work together. I’m happy to chat with anyone interested in medicine or urology.
