Incorporating Image-based Features into Biomedical Document Classification

September 14th, 2017 - August 31st, 2021

Categories: Applications, Visual Analytics, Visual Informatics, Deep Learning, Machine Learning, Data Science, Artificial Intelligence


This collaborative research project led by the colleagues at the University of Delaware aims to develop and advance tools for using image-data appearing in scientific publications, in addition to text, in order to support beneficial, targeted access to the biomedical literature.

UIC's principal investigator, Computer Science associate professor, G. Elisabeta Marai will be responsible for the image analysis algorithms to distinguish between gel and plate images, the image analysis algorithms to distinguish between Electronic Microscopy vs Fluorescent Microscopy vs Light Microscopy and X-Rays, and the design of the visual interface to present results to end users. She will lead the design, development and implementation of the feature extraction and selection tools and techniques related to this research project.