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 |
|---|---|---|---|---|---|
| Metabolomics Profiles for Colorectal Cancer Risk Prediction within prospective Cohorts in th COMETS Consortium | Jennifer Ose | Huntsman Cancer Institute, University of Utah | PLCO | Oct 31, 2017 | PLCO-320 |
| Meta-data for CRDC pilot study | Eric Miller | National Cancer Institute | PLCO | Dec 9, 2022 | PLCO-1128 |
| Meta-learning from digital pathology images for pancancer applications. | Olivier Gevaert | Stanford University | PLCO | Aug 7, 2019 | PLCO-493 |
| Methodologic research for stochastic models of colorectal cancer in natural history and under screening | Hormuzd Katki | NCI | PLCO | Sep 27, 2017 | PLCO-308 |
| Methodologies for modeling clinical performance and utilities of a cancer screening test using NLST trial as an example | James Dai | GRAIL LLC | NLST | Jul 3, 2023 | NLST-1090 |
| Methods for Early Detection of Lung Cancer | Rok Sosic | Stanford University | NLST | Dec 28, 2018 | NLST-461 |
| Methods for Etiologic and Early Marker Investigations | Richard Hayes | NCI, DCEG, OEEB | PLCO | Jul 1, 2006 | 2006-0130 |
| Methods for ovarian cancer risk prediction with longitudinal CA125 biomarker | Danping Liu | National Cancer Institute | PLCO | Feb 26, 2018 | PLCO-347 |
| Methods study for number of controls per case to choose in GWAS | Hormuzd Katki | NCI | PLCO | Apr 13, 2023 | PLCO-1200 |
| Microsimulation Model for Lung Cancer Screening: Calibration, Validation and Application | Sylvia Plevritis | Stanford University | NLST | Sep 9, 2013 | NLST-34 |
| Microsimulation model for lung cancer screening in New Zealand | Nokuthaba Sibanda | Victoria University of Wellington | NLST | Jul 14, 2022 | NLST-935 |
| Microsimulation model of a risk-based lung cancer screening program | Jacopo Di Silvestre | University of Oslo | NLST | Jan 26, 2024 | NLST-1191 |
| Minibatch Gradient Descent Method for Deep Survival Analysis | James Sharpnack | University of California-Davis | NLST | Nov 7, 2019 | NLST-597 |
| Missing censoring indicators in survival analysis | Mikael Escobar-Bach | Laboratoire Angevin de Recherche en Mathématiques, Université d'Angers | PLCO | Jan 18, 2023 | PLCO-1149 |
| Mitigating measurement error and missing data impact on analysis of food frequency questionnaire data using machine learning methods | Jennifer Frediani | Emory University | IDATA | Aug 22, 2022 | IDATA-56 |
| Mitochondrial DNA Copy Number and Prostate Cancer Risk | Sonja Berndt | NCI, DCEG, OEEB | PLCO | Mar 9, 2011 | 2011-0037 |
| Mobile Based Breast Cancer Diagnosing System Using a Rough Set-Ensemble Classifier Approach | Arthur Rahming | Philander Smith University | PLCO | Feb 14, 2024 | PLCO-1478 |
| Modeling and estimating a PSA threshold for prostate cancer diagnosis | Mei-Ling Lee | University of Maryland | PLCO | Feb 3, 2016 | PLCO-189 |
| Modeling lung cancer risk with Gradient-Boosted Decision-Trees | Jean-Emmanuel Bibault | INSERM UMR 1138 Team 22: Information Sciences to support Personalized Medicine, Cordeliers Research Centre, Paris Descartes University, Paris, France | NLST | Jul 15, 2021 | NLST-814 |
| Modeling progression of screening detected Lung Cancer | Olga Gorlova | UT MD Anderson Cancer Center | NLST | Dec 17, 2012 | NLST-8 |