Urodynamic Data and Machine Learning

Project Summary

A team of students led by Drs. Aquino (Engineering) and Routh (Urologic Surgery) will develop objective algorithms in order to guide data interpretation from a urology test, known as urodynamics, which is used in children with spina bifida in order to define a patient’s risk of debilitating bladder and kidney complications.  Urodynamics involves dynamic pressure monitoring as the bladder is filled with fluid.  This project is part of a 21-institution collaboration coordinated and funded by the U.S. Centers for Disease Control and Prevention (CDC), with the long-term goal of defining optimal management strategies for children with spina bifida. The short-term goal of this Data+ application is to define initial features of urodynamics that can be applied to increasingly complex future algorithms in order to guide clinical interpretations that determine whether, for example, children need reconstructive surgery in order to avoid complications of their disease.

Faculty Leads: Wilkins Aquino, Jonathan Routh

Project Manager: Zekun Cao

Themes and Categories
Year
2019
Contact
Paul Bendich
Mathematics
bendich@math.duke.edu

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