P-24 Mobile Application for Biosensor Colorimetric Analysis

Inexpensive paper-based biosensors can be valuable screening tools to test for various illnesses, but it is often challenging to design them to produce a visual change that can easily be identified by untrained users. This research aims to compensate for the lack of distinct visual cues by developing a mobile application that will use machine learning to analyze a picture of a sensor and determine whether it shows a positive or negative result. The machine learning algorithm will be trained on a set of labeled sensor images and its classification accuracy will be calculated and compared to a human expert