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 |
|---|---|---|---|---|---|
| Predicting lung cancer from clinical data and evaluating simulated screening programs | Adam Yala | The Regents of the University of California, on behalf of its Berkeley campus | PLCO | Sep 5, 2023 | PLCO-1316 |
| Predicting lung cancer patient outcomes using pathological imaging | Yang Xie | UT Southwestern Medical Center | NLST | Mar 6, 2014 | NLST-62 |
| Predicting lung cancer prognosis with deep learning | Francesco Ciompi | Radboud University Medical Center | NLST | Jun 30, 2017 | NLST-325 |
| Predicting lung cancer recurrence with machine learning | Flavio Calmon | Harvard University | NLST | Sep 10, 2019 | NLST-567 |
| Predicting lung cancer recurrence with machine learning | Flavio Calmon | Harvard University | PLCO | Sep 20, 2019 | PLCOI-522 |
| Predicting Lung Cancer Treatment Using an End to End 3D Serial Imaging CNN Model | Amy Li | Princeton University | NLST | Dec 11, 2019 | NLST-618 |
| Predicting medical outcomes using deep learning with CT chest images | Lyle Palmer | University of Adelaide | NLST | Jun 8, 2017 | NLST-311 |
| Predicting Mortality and Causes from Chest CT Images | david wilson | UPMC | NLST | Mar 9, 2021 | NLST-762 |
| Predicting mortality risk using cardiac LDCT regions | chen yingchi | National Yang Ming Chiao Tung University | NLST | May 16, 2024 | NLST-1255 |
| Predicting outcome of lung cancer patients using deep learning | Andreas Kleppe | Institute for Cancer Genetics and Infomatics, Oslo University Hospital | NLST | Mar 22, 2021 | NLST-772 |
| Predicting overall survival using CT and pathological image features | Peng Huang | Johns Hopkins University | NLST | Apr 21, 2016 | NLST-214 |
| Predicting Pancreatic Cancer Using Machine Learning and Neural Networks | Isaac Schwabe | University of Reading | PLCO | Jan 27, 2025 | PLCO-1801 |
| Predicting patient outcomes with machine learning of cancer histopathology images | Moritz Gerstung | EMBL-EBI | PLCO | Mar 21, 2019 | PLCO-463 |
| Predicting Progression of Lung Lesions on CT scans | Sendhil Mullainathan | University of Chicago | NLST | Sep 6, 2019 | NLST-560 |
| Predicting Prostate cancer Tissue type with machine learning | Md. Salman Karim Khan | Chittagong Medical College | PLCO | Jan 17, 2024 | PLCO-1450 |
| Predicting Pulmonary Function Abnormalities with a Texture-Based Quantification of Normal Lung Parenchyma in Chest Computed Tomography | Alysson Carvalho | ID'Or Institute Research and Education | NLST | Apr 2, 2024 | NLST-1223 |
| Predicting risk of cancer in 12 sites using the screened arm of the PLCO | Grant Izmirlian | National Cancer Institute | PLCO | Apr 5, 2021 | PLCO-762 |
| Predicting survival and molecular expression from histological images in lung cancer | Gil Shamai | Technion Research and Development Foundation Ltd | NLST | Nov 17, 2020 | NLST-727 |
| Predicting the location and interval of lung nodule occurrence from low-dose CT | Matthew Blackledge | Institute of Cancer Research | NLST | Apr 4, 2019 | NLST-493 |
| Predicting time to castration resistance in hormone sensitive prostate cancer | Ari Robinson | The Institute for Medical BioMathematics (IMBM) | PLCO | Oct 22, 2020 | PLCO-677 |