Author Tim Keyes is an M.D./Ph.D. student in Stanford's Medical Scientist Training Program.
As an M.D.-Ph.D. student whose research is more focused on machine learning and algorithmic development than on biology outright, I've spent a fair amount of time thinking about the seeming disconnect between the skills I need for research and the skills I'll need to provide good clinical care as a future doctor.
My research focuses on building predictive models of treatment response and relapse in pediatric cancer, so I spend most of my time writing R and Python code that wrangles, visualizes, and models data collected from patients. Yet despite spending most of my time programming, I know for a fact that coding is not in the top 20 (. . . or maybe top 100) skills needed to care for patients in a clinical environment.
Still, a few years of experience in both contexts has shown me that some lessons I've learned from being a programmer generalize wonderfully into my life as a medical student — and bode well for my future balancing these two worlds.
Here are a few of my insights.
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