Award-winning Machine Learning Algorithm

Mentor profile
Federal Agency, Research Fellow
University of Washington, Postbaccalaureate Fellow in Neuroengineering
Private tutor,
University of Washington, BA & BS
Project description

Every year, 60,000 Americans are diagnosed with Parkinson’s disease (PD), a progressive neural disease that causes mental degeneration. Signs of this can often be seen in distorted speaking patterns such as slurred words and mumbling. In this Polygence project, the student made a machine learning algorithm that uses speech features to predict whether a patient has PD. Building off of an automatic voice recording and segmentation tool, this student developed a fully automated, intelligent system capable of early detection and diagnosis of PD.

Project outcome

This student won 2nd place in the computer science category at the Alameda County Science and Engineering Fair!

Check out this student's project!
Student background

10th grader from California.

Student review

Polygence was an incredible introduction to research as a high schooler. Working one-on-one with my mentor taught me many valuable techniques and key steps in making machine learning projects. I enjoyed learning about ways to process data and use different algorithms to make accurate predictions off of it. Near the end of the program, using academic writing to present my findings was also a great way to learn about standards for publishing research in the field. I can definitely say that Polygence has empowered me to pursue research in the intersection of machine learning and medicine beyond the program.

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