G. Caleb Alexander, MD, MS is a Professor of Epidemiology and Medicine at Johns Hopkins Bloomberg School of Public Health, where he serves as a founding co-Director of the Center for Drug Safety and Effectiveness and Principal Investigator of the Johns Hopkins Center of Excellence in Regulatory Science and Innovation (CERSI). He is a practicing general internist and pharmacoepidemiologist and is internationally recognized for his research examining prescription drug utilization, safety and effectiveness.
PI: G. Caleb Alexander, MD (Bloomberg School of Public Health)
Co-I: Anqi Liu
We propose to develop state-of-the-art computer-vision software to rapidly and efficiently identify compelling visual artifacts in the Opioid Industry Documents Archive (OIDA), a highly innovative document collection focused on the U.S. opioid epidemic.
Specifically, we have three objectives:
- To improve OIDA’s current Python code for extracting images from PowerPoint and Excel documents to filter out the smallest, least meaningful images
- To develop new code that uses computer vision to detect images within raster PDFs, which comprise the vast majority of documents in the OIDA dataset
- To develop a supervised machine-learning pipeline to select from among the extracted images those that are most meaningful for sharing in an online gallery
