Poster 30: Tyler Gee – Machined Learning of Breath-based Volatile Organic Compound Sensors for Improved Diagnosis

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Faculty mentor: Swomitra Mohanty

Titanium Oxide sensors developed by Dr. Mohanty and his team are being used to diagnose TB patients in Uganda. The patient breath samples for diagnosis needed a way to be analyzed and to aid in diagnosis. Two types of tests were done amperometry and cyclic voltammetry. Originally machine learning was the proposed method however numerical methods proved more effective. The hypothesized signals ended being inconclusive due to the small sample size and nature of pediatric samples.

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Questions or comments? Contact me at: u0885370@utah.edu

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