Regulatory Science Tools Catalog
The Regulatory Science Tools Catalog provides a peer-reviewed resource for use where standards and qualified Medical Device Development Tools (MDDTs) do not yet exist. These tools do not replace FDA-recognized standards or MDDTs. This catalog collates a variety of regulatory science tools that the FDA's Center for Devices and Radiological Health's (CDRH) Office of Science and Engineering Labs (OSEL) developed. If you are considering using a tool from this catalog in your marketing submissions, note that these tools have not been qualified as Medical Device Development Tools and the FDA has not evaluated the suitability of these tools within any specific context of use. You may request feedback or meetings for medical device submissions as part of the Q-Submission Program.
This regulatory science tool (RST) is a software program written in Python for performance assessment of segmentation algorithms applied to digital pathology whole slide images (WSIs).
This regulatory science tool presents two methods to amplify Artificial Intelligence (AI) / Machine Learning (ML) model bias to enable the evaluation of bias mitigation methods on models with varying amounts of performance bias.
This regulatory science tool presents a method (DRAGen) that identifies the types of errors which Artificial Intelligence (AI) / Machine Learning (ML) medical image classification algorithms might make when used on new populations.
This regulatory science tool presents a method (web-based decision tree) that may help developers select appropriate metric and endpoint for Artificial Intelligence (AI) / Machine learning (ML) classification algorithms in medical imaging.
Tools that quantify wait-time-saving benefits for cases with positive diagnoses due to the adoption of Computer-Aided Triage and Notification devices in a radiology workflow