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High-throughput Truthing

by Brandon D. Gallas

This project is generally open to new participants.

We will use the eeDAPstudies NCIPhub group to coordinate communications. So if you are a member, you will receive related communications about that project in addition to communications about the eeDAP MDDT. If you are not a member, sign up or check for updates here and in the blog. Updates will also be provided to the WSI working group on a less frequent basis.

Year 2: High-throughput truthing of microscope slides to validate artificial intelligence algorithms analyzing digital scans of pathology slides: data (images + annotations) as an FDA-qualified medical device development tool (MDDT).

Year 1: High-throughput truthing of microscope slides to validate artificial intelligence algorithms analyzing digital scans of pathology slides: leveraging data collected in international “grand challenges”.

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