Drexel University

    Make use of machine learning to help pathologists identify the density of the eosinophil cells in digital slides of human nasal tissue.

    Back in 2018, a team of Drexel students began their work on leveraging the power of computer neural networks in an effort to reduce the time-consuming activity of analyzing digital slides by pathologists. Partnering with the pathology department at the University of Pennsylvania, they collected data, built interfaces to help pathologists categorize the data, and made great steps towards achieving their goal of creating a tool to output the density of the eosinophil cells in digital slides of human nasal tissue. 
    The new 2019/2020 Digital Pathology team is working to continue the project the original team laid out. By analyzing, reworking, and expanding upon the original code base, the current Digital Pathology team looks to improve the original project both in accuracy of cell detection and in identification time to where practicing pathologists may benefit from the use of the tool in actual medical cases.