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---
layout: home
title: High Throughput Truthing Project
subtitle: FDA DIDSR validation dataset creation for ML algorithm development.
---
<body>
<section>
<menu>
<h2><strong>Key Pages</strong></h2>
<ul>
<li><a href="./assets/pages/whatIsHTT">What is the HTT project?</a></li>
<li><a href="./assets/pages/training-2023">Training Materials</a></li>
<li><a href="./assets/pages/pivotal-study">Pivotal Study</a></li>
<li><a href="./assets/pages/publications">Publications</a></li>
<li><a href= "./assets/pages/disclaimer">Commercial Products Disclaimer</a></li>
<li><a href= "./assets/pages/infoMedicalImagingAIregulatorySubmissions">Regulatory Submission Information For Developers</a></li>
</ul>
</menu>
<article>
<p>The HTT project aims to create a validation dataset established by pathologist annotations for artificial
intelligence
algorithms analyzing digital scans of pathology slides: data (images + annotations). We are pursuing the
qualification
of the final validation dataset as an FDA-qualified medical device development tool MDDT to become a
high-value public
resource that can be used in AI/ML algorithm submissions and guide others to develop quality validation
datasets.
</p>
<p>This site is new. We are moving here from our <a
href="https://ncihub.cancer.gov/groups/eedapstudies">original
(legacy) project home on the NCI hub</a>.
Please be patient with this process. We are happy to get feedback and questions. <a
href="./assets/pages/team">Email the project team.</a></p>
</article>
</section>
</body>
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