The Innovative Methodologies and New Data for Predictive Oncology Model Evaluation (IMPROVE) project was created under the Cancer Moonshot℠ as part of the NCI-DOE Collaboration to help address the need in the AI modeling community for a robust, reproducible, fair, and transparent way to compare AI models at scale. IMPROVE is intended to help address challenges in data-driven modeling for predicting cancer drug response by establishing consistent methodologies for model comparison and evaluation, and by enhancing machine learning models through novel data integration. IMPROVE also generates new data to reduce bias and improve performance based on the deficiencies seen in the current AI models we are testing. These data will be available to the public to improve future drug response models.
You can take a look at our documentation for more information about the project and examples of applying the framework.
Current release:
- Status: pre-production release
- Version: v0.2.0-beta
- Summary: https://github.com/JDACS4C-IMPROVE/Singularity/releases/tag/v0.2.0-beta