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 |
|---|---|---|---|---|---|
| Lung Cancer Detection using Data Analytics and Machine Learning | Apoorva Mahale | Vivekanand Education Society's Institute of Technology | NLST | Jan 30, 2017 | NLST-277 |
| Lung cancer prediction by deep learning approach | Xiaokang Wang | University of California,Davis | NLST | Jan 26, 2017 | NLST-273 |
| Continued deep learning modeling for early detection | Jeremy Howard | University of San Francisco | NLST | Jan 25, 2017 | NLST-274 |
| Melanoma Data Analysis2 | Hovig Devejian | FSU | PLCO | Jan 24, 2017 | PLCO-253 |
| Request for access to the Ovarian Biomarkers data in order to correlate values with those obtained on our multiplex platform | Amy Skubitz | University of Minnesota | PLCO | Jan 20, 2017 | PLCO-254 |
| Absolute Risk Model Evaluation and Integration of Imaging Biomarkers for Early Detection and Risk Assessment of Cancer | Jae Lee | Moffitt Cancer Center | PLCO | Jan 12, 2017 | PLCO-248 |
| Examining Trends in Prostate Cancer Diagnosis, Treatment and Mortality | D. Duane Baldwin | Loma Linda University Health | PLCO | Jan 12, 2017 | PLCO-247 |
| Physical activity and reproductive characteristics in the development of postmenopausal breast cancer | Chuanbo Xie | Sun Yat-sen University Cancer Center | PLCO | Jan 10, 2017 | PLCO-249 |
| Diet and risk of glioma in the PLCO Study | Ai-Seon Kuan | Cancer Epidemiology Unit, University of Oxford | PLCO | Jan 5, 2017 | PLCO-252 |
| SPORE Grant Pipeline | Paul Kinahan | University of Washington | NLST | Jan 5, 2017 | NLST-271 |
| Lung nodule characterization using machine learning techniques | Jack Lin | N/A | NLST | Jan 4, 2017 | NLST-270 |
| Intelligent Lung Cancer Diagnostic Aid System: a RADIOMICS approach applied to histology | Lucas Lima | Federal University of Alagoas | NLST | Dec 27, 2016 | NLST-268 |
| Application of machining learning in lung cancer prediction with the NLST and PLCO data | Liang Ge | Diannai (Shanghai) Biotech Co., Ltd. | PLCO | Dec 27, 2016 | PLCO-250 |
| Application of machining learning in lung cancer prediction with the NLST and PLCO data | Liang Ge | Diannai (Shanghai) Biotech Co., Ltd. | NLST | Dec 27, 2016 | NLST-269 |
| Risk modelling of time to lung cancer diagnosis | Anton Schreuder | Radboudumc | NLST | Dec 27, 2016 | NLST-267 |
| Medical data mining on small datasets | Ron Wolfslast | University Hamburg | NLST | Dec 16, 2016 | NLST-266 |
| Lifestyle changes after a cancer diagnosis in relation to all-cause and cancer-specific mortality | Hannah Brooke | Karolinska Institutet | PLCO | Dec 16, 2016 | PLCO-245 |
| MRI screening for lung cancer: Markov modeling using the NLST CT outcomes data | Mark Schiebler | UW-Madison School of Medicine and Public Health | NLST | Dec 15, 2016 | NLST-265 |
| Early detection of lung cancer with deep neural nets | weiyi xie | JianPei technology, Ltd | NLST | Dec 13, 2016 | NLST-260 |
| Diabetes, PSA levels and prostate cancer screening outcomes | Eric Miller | NCI | PLCO | Dec 12, 2016 | PLCO-246 |