Approved NLST Projects
Here you can browse the complete list of projects for NLST whose requests for data/biospecimens were approved.
| Name | Principal Investigator | Institution | Study | Date Approved | Project ID |
|---|---|---|---|---|---|
| Automated Lung Nodule Detection using Deep Neural Networks | Kun-Hsing Yu | President and Fellows of Harvard College | NLST | Feb 22, 2017 | NLST-286 |
| Building a Common Data Model for Cancer Research | Guoqian Jiang | Mayo Clinic | NLST | Feb 17, 2017 | NLST-285 |
| Pulmonary Nodule Detection and Classification using large scale CT data | feifei zhou | Independent Researcher, not applicable | NLST | Feb 13, 2017 | NLST-283 |
| Radiomics using Deep Learning with High Performance Computing | Eduardo Ulises Moya Sánchez | Barcelona Supercomputing Center | NLST | Feb 9, 2017 | NLST-275 |
| Improvement of Early Lung Cancer Detection Rate for Patients Undergoing 18F-FDG PET/CT scans | Tsung-Ying Ho | Chang Gung Memorial Hospital | NLST | Feb 9, 2017 | NLST-284 |
| Surgical approach and outcomes in NLST patients with positive screening CT | Brendon Stiles | Weill Cornell Medicine | NLST | Feb 7, 2017 | NLST-281 |
| Medical applications of example-based super-resolution | Ramin Zabih | Joan & Sanford I. Weill Medical College of Cornell University | NLST | Jan 31, 2017 | NLST-279 |
| Deep learning of lung cancer images for segmentation and outcome prediction | Olivier Gevaert | Stanford University | NLST | Jan 31, 2017 | NLST-276 |
| Lung lesion screening and tracking | Carla Leibowitz | Arterys | NLST | Jan 30, 2017 | NLST-278 |
| 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 |
| SPORE Grant Pipeline | Paul Kinahan | University of Washington | NLST | Jan 5, 2017 | NLST-271 |
| Intelligent Lung Cancer Diagnostic Aid System: a RADIOMICS approach applied to histology | Lucas Lima | Federal University of Alagoas | NLST | Dec 27, 2016 | NLST-268 |
| 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 |
| 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 |
| Instance-driven semantic segmentation and clinical information assessment of temporal changes for lung nodules | Kang Li | Department of Industrial and Systems Engineering | NLST | Dec 5, 2016 | NLST-261 |
| RETROSPECTIVE ANALYSIS OF PULMONARY NODULES USING A NEW ALGORITHM FOR DETERMINING INTERVAL GROWTH, WITH SUBSEQUENT PROSPECTIVE ANALYSIS FOR BLINDED VALIDATION | John Billings | Independent Researcher | NLST | Dec 5, 2016 | NLST-263 |
| Automatic lung nodule detection by CNN | Shuang Wu | Yitu USA | NLST | Dec 2, 2016 | NLST-258 |