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 |
|---|---|---|---|---|---|
| Validating the performance of Deep Neural Network models for lung nodule detection | Naglis Ramanauskas | Oxipit, UAB | NLST | Feb 16, 2022 | NLST-886 |
| A Deep Learning Model for Improved Cancer Risk Prediction in Sequential Lung Screening X-Rays | Regina Barzilay | Massachusetts Institute of Technology | NLST | Feb 16, 2022 | NLST-885 |
| Building integrative multi-modal and interpretable AI systems for personalized lung cancer therapy | Ruijiang Li | Stanford University | NLST | Feb 16, 2022 | NLST-884 |
| Optimization of lung cancer screening interval by deep learning-based risk prediction | Adam Alessio | Michigan State University | NLST | Feb 16, 2022 | NLST-883 |
| Personalised lung cancer treatment through outcome predictions and patient stratification | Charles-Antoine Collins Fekete | University College London | NLST | Feb 16, 2022 | NLST-881 |
| Progression prediction of lung cancer using deep learning model | Sunghoon Kwon | Seoul National University | NLST | Feb 2, 2022 | NLST-879 |
| Assessing the Generalizability of Findings from the NLST | Louise Henderson | University of North Carolina at Chapel Hill | NLST | Jan 26, 2022 | NLST-876 |
| Development and validation of a neural network to detect and describe lung nodules | Alexandre Compas | Gleamer SAS | NLST | Jan 26, 2022 | NLST-878 |
| Lung Abnormality Detection using Deep learning | Harshil Soni | System Level Solutions India Ptv.Ltd. | NLST | Jan 26, 2022 | NLST-875 |
| Fully automated end to end analysis of non-small-cell lung carcinoma using deep learning techniques | Eranga Ukwatta | University of Guelph | NLST | Jan 26, 2022 | NLST-871 |
| Unsupervised analysis of thorax CT datasets | Marian Himstedt | University of Luebeck | NLST | Jan 18, 2022 | NLST-870 |
| Federated Validation of Lung Nodule Detection Algorithms. | Brian Ayers | Gesund AI | NLST | Jan 18, 2022 | NLST-869 |
| Pulmonary Adenocarcinoma of Low Malignant Potential | Eric Burks | Boston University School Of Medicine | NLST | Jan 7, 2022 | NLST-867 |
| Lower level of education matters when it comes to compliance to lung cancer screening | Akeel Alali | King Abdullah International Medical Research Center’s (KAIMRC) and King Saud bin Abdulaziz university for health sciences | NLST | Nov 30, 2021 | NLST-856 |
| The benefits and harms of lung cancer screening in Florida | Dr. Yi Guo | University of Florida Board of Trustees | NLST | Nov 30, 2021 | NLST-857 |
| Health economic evaluation for lung cancer screening alone or combined with screening for emphysema and coronary calcium scoring | Hendrik Koffijberg | University of Twente | NLST | Nov 15, 2021 | NLST-852 |
| Analysis of screening technology performance and patient demographics to improve blood-based early lung cancer detection | Toumy Guettouche | Mercy BioAnalytics | NLST | Nov 15, 2021 | NLST-851 |
| Modified Lung-RADS classification incorporating nodule risk calculator. | Alain Tremblay | THE GOVERNORS OF THE UNIVERSITY OF CALGARY | NLST | Nov 5, 2021 | NLST-849 |
| Validation of Automated Lung Nodule Detection, Segmentation, and Matching | Samuel Peterson | VIDA Diagnostics, Inc | NLST | Nov 3, 2021 | NLST-848 |
| Self-selection and decision to participate in clinical trials: evidence from screening trials | Hualong Diao | Stony Brook University | NLST | Nov 3, 2021 | NLST-845 |