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 |
|---|---|---|---|---|---|
| Detection and Diagnosis of Lung Cancer with Deep Learning | Shan Li | Zephex Technology | NLST | Mar 21, 2017 | NLST-295 |
| Computer aided diagnosis for radiology and histopathology images | zhenhua xu | Independent Researcher, not applicable | NLST | Mar 15, 2017 | NLST-293 |
| Automatic Early Lung Cancer Detection with Deep Neural Networks | Jackie Jiang | Wingspan Technology | NLST | Feb 22, 2017 | NLST-287 |
| 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 |
| 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. | NLST | Dec 27, 2016 | NLST-269 |
| Risk modelling of time to lung cancer diagnosis | Anton Schreuder | Radboudumc | NLST | Dec 27, 2016 | NLST-267 |