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 |
|---|---|---|---|---|---|
| Optimize radiological workflows with automated diagnostics | Daniel Drieling | MeVis Medical Solutions AG | NLST | Mar 29, 2019 | NLST-491 |
| Quantitative CT Analysis to Predict Future Lung Cancer | TIMOTHY CLOUSER | Quantitative Imaging Solutions, LLC | NLST | Mar 29, 2019 | NLST-490 |
| Gender-specific susceptibility and hormonal influence on lung cancer incidence | Juan Wisnivesky | Icahn School of Medicine at Mount Sinai | PLCO | Mar 25, 2019 | PLCO-460 |
| Predicting patient outcomes with machine learning of cancer histopathology images | Moritz Gerstung | EMBL-EBI | PLCO | Mar 21, 2019 | PLCO-463 |
| Neural Network Application in Medical Research with Concentration on Breast Cancer | Chenying Lu | Harrisburg University | PLCO | Mar 21, 2019 | PLCO-462 |
| Risk factor epidemiology of thyroid cancer | Omar Abdel-Rahman | Avicenna Oncology center | PLCO | Mar 8, 2019 | PLCO-458 |
| Gender-specific susceptibility and hormonal influence on lung cancer incidence | Juan Wisnivesky | Icahn School of Medicine at Mount Sinai | NLST | Mar 6, 2019 | NLST-487 |
| The role of BMI in upgrading and upstaging of men with clinically localized prostate cancer | Kathryn Barry | University of Maryland, Baltimore | PLCO | Feb 28, 2019 | PLCO-455 |
| Evaluating the Potential for Biomarker Use in CT Screening | Hilary Robbins | International Agency for Research on Cancer (IARC) | PLCO | Feb 20, 2019 | PLCO-456 |
| Machine Learning Classification of Nodules | Michal Lada | University of Rochester | NLST | Feb 19, 2019 | NLST-484 |
| Lung cancer case prioritization tool with automated CT scan classification | Ramune Dauksaite | Birkbeck College, University of London | NLST | Feb 19, 2019 | NLST-483 |
| Prediction of NSCLS from CT scan and habitual data of a person after two years by using CNN and LSTM machine learning techniques | Mayur Munshi | University of Manchester | NLST | Feb 14, 2019 | NLST-481 |
| Self-reported dietary intake and serum metabolite correlations | Kaitlyn Mazzilli | National Cancer Institute | PLCO | Feb 13, 2019 | PLCO-454 |
| Ovarian cancer identification using machine learning techniques | Julius Ting | Asia Pacific University | PLCO | Feb 11, 2019 | PLCO-452 |
| Feature Selection for Survival Analysis with Competing Risks using Deep Learning | Mihaela van der Schaar | University of California, Los Angeles | PLCO | Feb 11, 2019 | PLCO-453 |
| Light at night and prostate cancer risk and progression | Lorelei Mucci | Harvard University | PLCO | Feb 11, 2019 | PLCO-433 |
| Therapixel-AI | Stephanie Lopez | Therapixel | NLST | Feb 5, 2019 | NLST-478 |
| Incorporating gender differences in lung cancer screening | Kevin ten Haaf | Erasmus MC | NLST | Feb 4, 2019 | NLST-480 |
| Data-driven Imaging Biomarker (DIB) study in NLST datasets | Ki Hwan Kim | Lunit | NLST | Feb 1, 2019 | NLST-474 |
| The link between diabetes status and pancreatic Cancer survival | Sabrina Benteftifa | Independent | PLCO | Feb 1, 2019 | PLCO-451 |