Here you can browse the complete list of projects for NLST whose requests for data/biospecimens were approved.
Filter results of approved projects table below
| Name | Principal Investigator | Institution | Study | Date Approved | Project ID |
|---|---|---|---|---|---|
| Coronary artery calcification quantification | Joris Wakkie | Aidence | NLST | May 28, 2019 | NLST-514 |
| Longitudinal analysis of lung diseases using CT and pathology images | Vaishnavi Subramanian | University of Illinois at Urbana-Champaign | NLST | May 22, 2019 | NLST-512 |
| Building a Deep Learning prediction model using CT images and patient characteristics | Jagdeep Podichetty | Critical Path Institute | NLST | May 22, 2019 | NLST-511 |
| Development of radiomic models for lung nodule diagnosis | Binsheng Zhao | Columbia University Medical Center | NLST | May 7, 2019 | NLST-507 |
| Validation of a standardized semiquantitative template for reporting cardiac abnormalities on thoracic CT examinations of patients with non-cardiac disease | Alexander Bankier | University of Massachusetts Medical School | NLST | May 1, 2019 | NLST-506 |
| Lung Screening: Efficacy versus Effectiveness | Ilana Gareen | Brown University | NLST | Apr 29, 2019 | NLST-505 |
| Lung lesions segmentation and cancer prediction | Ha Nguyen | Vingroup Big Data Institute | NLST | Apr 29, 2019 | NLST-504 |
| Population wide sarcopenia and sarcopenic obesity analysis | Andrew Green | The University of Manchester | NLST | Apr 17, 2019 | NLST-497 |
| Detection and prognosis of lung cancer with deep learning | Daniel Truhn | RWTH Aachen University | NLST | Apr 16, 2019 | NLST-500 |
| Cisco Validated Design reference architecture for SAS Artificial Intelligence / Machine Learning | Andrew Lockhart | SAS | NLST | Apr 13, 2019 | NLST-499 |
| Evaluating genetic, clinical, and environmental risk factors for second primary lung cancer | Summer Han | Stanford University | NLST | Apr 13, 2019 | NLST-498 |
| Automatic Coronary Calcium Scoring on both chest and cardiac CT using deep learning | Yufeng Deng | Infervision US Inc. | NLST | Apr 9, 2019 | NLST-496 |
| Machine learning based lung cancer identification and characterization | Richard Vlasimsky | IMIDEX | NLST | Apr 5, 2019 | NLST-495 |
| 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 |
| Out of pocket costs associated with Lung Cancer Screening | Daniel Reuland | University of North Carolina at Chapel Hill Comprehensive Cancer Center | NLST | Apr 2, 2019 | NLST-492 |
| 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 | NLST | Mar 6, 2019 | NLST-487 |
| 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 |