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 |
|---|---|---|---|---|---|
| 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 |
| 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 |
| Early detection of lung cancer with deep neural nets | weiyi xie | JianPei technology, Ltd | NLST | Dec 13, 2016 | NLST-260 |
| 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 |
| Early Detection and Prognosis of Lung Cancer | Yun Li | UNC Chapel Hill | NLST | Dec 2, 2016 | NLST-262 |
| Statistical models to predict future subject’s lung cancer risk: application to NLST and PLCO data | Ping Hu | NCI | NLST | Nov 21, 2016 | NLST-259 |
| Clinical Decision Support System (CDSS) and self-learning tool for radiologists for Lung CT using Content Based Image Retrieval (CBIR). | Sudipta Mukhopadhyay | Indian Institute of Technology Kharagpur, India | NLST | Nov 10, 2016 | NLST-255 |
| Longitudinal Deep Radiomic Signatures for Lung Cancer Prognosis and Treatment Response Prediction | Nicolas Chapados | Imagia Inc. | NLST | Nov 10, 2016 | NLST-256 |
| Tumor early detection and prognosis | Hongtu Zhu | University of Texas MD Anderson Cancer Center | NLST | Nov 3, 2016 | NLST-254 |