Approved Projects
Here you can browse the complete list of projects on CDAS whose requests for data/biospecimens were approved.
| Name | Principal Investigator | Institution | Study | Date Approved | Project ID |
|---|---|---|---|---|---|
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | MAYO | Nov 14, 2024 | MAYO-5 |
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | JHLP | Nov 14, 2024 | JHLP-4 |
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | MINN | Nov 14, 2024 | MINN-6 |
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | MEM | Nov 14, 2024 | MEM-7 |
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | HIPB | Nov 14, 2024 | HIPB-15 |
| Improved Methods for Comparing Human Radiologists to AI tools | Ashesh Rambachan | Massachusetts Institute of Technology | NLST | Nov 12, 2024 | NLST-1357 |
| Machine Learning approach for the analysis of lung cancer data to aid the radiologists at global level | Tiratharaj Singh | Jaypee University of Information Technology (JUIT) | NLST | Nov 12, 2024 | NLST-1355 |
| Exploring Multimodal Factors Influencing Breast Cancer Risk: A Data-Driven Approach | Oliver Díaz | Universitat de Barcelona | PLCO | Nov 12, 2024 | PLCO-1742 |
| A Hybridized machine learning based survival prediction of ovarian cyst | Ovoh Oghenefego | Delta State University Abraka | PLCO | Nov 12, 2024 | PLCO-1740 |
| Identifying Survival Phenotypes in High-Grade Serous Ovarian Cancer by Application of AI to Digital Pathology | Ernst Lengyel | University of Chicago | PLCO | Nov 12, 2024 | PLCOI-1737 |
| Using deep learning models to infer spatial transcriptomics from H&E slides | Eytan Ruppin | Cancer Data Science Laboratory, NCI | NLST | Nov 5, 2024 | NLST-1353 |
| Comparing the accuracy of machine learning diagnosis of lung cancer from different data modalities | Polina Golland | Massachusetts Institute of Technology | NLST | Nov 5, 2024 | NLST-1349 |
| Radiomics-Driven Predictive Lung Cancer Models | Patrice Essien | George Washington University | NLST | Nov 5, 2024 | NLST-1347 |
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | NLST | Nov 5, 2024 | NLST-1345 |
| Quantification of Interstitial Lung Abnormalities Using Data from the National Lung Screening Trial | Hyungjin Kim | Seoul National University Hospital | NLST | Nov 5, 2024 | NLST-1350 |
| Surrogate endpoints for cancer screening trials | Adam Brentnall | Queen Mary University of London | LSS | Nov 5, 2024 | LSS-9 |
| Prostate Cancer Screening using Machine Learning | Jerry John Rawlings Mensah | Virginia Commonwealth University | PLCO | Nov 5, 2024 | PLCO-1732 |
| Science Fair | Caspar McNulty | Swanson Middle School | PLCO | Nov 5, 2024 | PLCO-1725 |
| Development of Models for Predicting Clinical Outcomes from H&E Stained Whole Slide Images | Zoltan Szallasi | Boston Children's Hospital | PLCO | Nov 5, 2024 | PLCOI-1720 |
| The growing incidence of of colorectal cancer among those under 55 years age in The United States | Harrinique Deveaux | Florida State University | PLCO | Nov 5, 2024 | PLCO-1727 |