Whole Slide Pathological Image Analysis Using Frederick Research Computing Environment

About this Class

Frederick Research Computing Environment (FRCE) and Computational Sciences Series

In this session, we will explore how machine learning can be used to analyze whole slide pathological images (WSIs). We will showcase how to utilize the Frederick Research Computing Environment (FRCE) to speed up processing using GPUs. Having a foundational understanding of machine learning or deep learning could be advantageous.

This session will be recorded, and materials will be posted on the Advanced Biomedical Computational Science training site and will also be shared with attendees a few days after the event. For details, please contact Natasha Pacheco, of the Advanced Biomedical Computational Science (ABCS) group at Frederick National Laboratory for Cancer Research.

If you are an individual with a disability who needs reasonable accommodations to participate in this event, please contact Natasha Pacheco at least five business days before the event, so that we can discuss your accommodation request.