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 |
|---|---|---|---|---|---|
| Technology Development of Deep Learning based Lung CT and Chest X-Ray Reading | Jing Xiao | Ping An Technology(Shenzhen) Company Ltd. | NLST | Sep 18, 2017 | NLST-345 |
| Improving accuracy in nodule detection and cancer prediction using data-driven deep learning approach | Yuan Feng | Shenzhen Vega Medical Technology Limited | NLST | Sep 18, 2017 | NLST-342 |
| Selecting the risk cut off for the LLP model. | Kevin ten Haaf | Erasmus MC | NLST | Aug 27, 2017 | NLST-343 |
| Machine learning to identify, track, and monitor disease | John MacLean | doclink.io | NLST | Aug 16, 2017 | NLST-338 |
| Predict histological grade by CT image auto-reviewing | Edwin Wang | University of Calgary | NLST | Aug 16, 2017 | NLST-340 |
| Predicting lung cancer from chest radiography features | Ashwini Suriyaprakash | Independent | NLST | Aug 7, 2017 | NLST-334 |
| Ultra-Low-Dose Lung Nodule CT Surveillance Using Prior-Image-Based Reconstruction | Hao Zhang | Johns Hopkins University | NLST | Aug 3, 2017 | NLST-329 |
| Interpretable machine learning models for lung cancer screening | Cynthia Rudin | Duke | NLST | Aug 2, 2017 | NLST-332 |
| image deep learning of lung cancer cell | Tang Wei | Chongqing University | NLST | Aug 1, 2017 | NLST-331 |
| Gist response | Patrick Brennan | University of Sydney | NLST | Jul 31, 2017 | NLST-333 |
| Role of Image Segmentation Methods in Increasing the Efficiency and Accuracy of Neural Networks in Cancer Detection | Zong Zhang | N/A | NLST | Jul 28, 2017 | NLST-335 |
| image reconstruction | YUNXI JIANG | SUN YAT-SEN UNIVERSITY | NLST | Jul 18, 2017 | NLST-327 |
| Enhancement of pulmonary nodule detection algorithm using large scale LDCT data | Seungho Lee | Vuno | NLST | Jul 10, 2017 | NLST-322 |
| Precision medicine via survival analysis | Yan Li | University of Michigan | NLST | Jul 6, 2017 | NLST-326 |
| Advanced Deep Learning for Early Detection and Prognostication in Lung Cancer | Zeng Zeng | Institute for Infocomm Research | NLST | Jul 5, 2017 | NLST-323 |
| Predicting lung cancer prognosis with deep learning | Francesco Ciompi | Radboud University Medical Center | NLST | Jun 30, 2017 | NLST-325 |
| Targeting low-dose CT to reduce mortality from lung cancer: a machine learning-based analysis of heterogeneous treatment effects in the NLST | Aaron Baum | Icahn School of Medicine at Mount Sinai | NLST | Jun 30, 2017 | NLST-324 |
| Using Big Data for Computer-Aided Diagnosis of Chest CTs | Ronald Summers | National Institutes of Health Clinical Center | NLST | Jun 30, 2017 | NLST-319 |
| Machine learning to differentiate between malignant and benign nodules | Parag Chaudhari | Mon Health Medical Center | NLST | Jun 22, 2017 | NLST-315 |
| Deep learning for lung nodule detection and cancer prediction | Quan Chen | University of Kentucky | NLST | Jun 22, 2017 | NLST-320 |