= 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). =
 * Notice the title change at the end. If we can "qualify" a data set via FDA/CDRH MDDT program, it will be available to developers to use as their pivotal validation data in a submission to the FDA. That's the primary aim of year 2.
 * Internal funding proposal submitted 10/19/2018. Decisions expected in March 2019
 * Link to Full Proposal for year 2 [[File(binderFY19_CDRH_CP_Application-GallasHighThroughputTruthingDigiPathPublic.pdf)]]

= Year 1: 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). =
 * Project was funded March 2018.
 * [https://nciphub.org/groups/eedapstudies/wiki/HighThroughputTruthing/HighThroughputTruthingYear1 Link to wiki page for year 1]