As a new law school graduate, I had about three months between taking the bar exam and starting a job as an associate at a law firm, and I was looking for an interesting project to take on in my free time. My boyfriend, Lester Mackey, PhD suggested that we work together on a competition that involved learning and data analysis; as a machine learning researcher, he had the experience to accompany my time and enthusiasm. This would give me the opportunity to participate in an exciting competition, and in the process, improve my coding skills and learn a little bit about Lester’s field of research.
We chose to work on the ALS Prediction Prize challenge because the goal of advancing the science behind the disease was so compelling. While we knew nearly nothing about the disease going in, working on the challenge showed us how devastating the effects of ALS can be. For example, the measure we were trying to predict, the ALS Functional Rating Scale, is comprised of ten questions that assess a patient’s ability to perform basic tasks like speaking or walking. Working closely with this data was a reminder that ALS patients face the continued degradation of these familiar abilities with each passing month. My involvement, then, led not only to a better understanding of statistical prediction but also to a heightened awareness of ALS.
Winning the ALS Prediction Prize challenge was a big surprise. It was enormously encouraging that we were able to have some impact in an area in which neither of us had any substantive expertise. This testifies to the merits of a crowdsourced model for innovation, which can empower individuals to make meaningful contributions in unfamiliar areas. Winning the challenge also gave us the opportunity to meet with other participants and the organizers from Prize4Life and DREAM. We were inspired by our discussions with these knowledgeable and dedicated people and came away with a better understanding of the context of our work.
Participating in the DREAM-Phil Bowen ALS Prediction Prize4Life challenge was an extraordinary experience. I’m equally thrilled by our ability to contribute to ALS and grateful for the insights it has brought me.