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 |
|---|---|---|---|---|---|
| Individual lung cancer survival estimation based on radiomics analysis | Yujiao Wu | University of Technology Sydney | NLST | Oct 31, 2019 | NLST-596 |
| use active learning to do the tumor segmentation. | Sijie Wang | the university of Tokyo | NLST | Oct 31, 2019 | NLST-595 |
| Interpretable Graph Convolutional Networks with CPC features for Whole Slide Histology Classification | Faisal Mahmood | Brigham and Women's Hospital | NLST | Oct 29, 2019 | NLST-592 |
| Exascale Deep Learning for Predictive Modeling of Lung Cancer | Greeshma Agasthya | Oak Ridge National Laboratory | NLST | Oct 18, 2019 | NLST-586 |
| Lung cancer imaging biomarker development on computed tomography using artificial intelligence | Shazia Akbar | Altis Labs | NLST | Oct 15, 2019 | NLST-588 |
| Application and evaluation of Deep Learning to Predict tumors in medical images annotated using crowdsourcing | Aakanksha Sanctis | Maastricht University,Intitute of Data Science | NLST | Oct 15, 2019 | NLST-587 |
| Intelligent personable treatment recommendation | Xiaoshui Huang | The University of Sydney | NLST | Oct 10, 2019 | NLST-584 |
| Lung cancer imaging biomarker development on computed tomography using artificial intelligence | Julia Publicover | University Health Network | NLST | Oct 8, 2019 | NLST-575 |
| A Comparative Analysis of Lung Cancer Treatment in a Local and National Sample with Lung Cancer | Lee Ann Johnson | East Carolina University | NLST | Oct 4, 2019 | NLST-581 |
| Development and validation of a computer-aided diagnosis system for lung cancer screening | CHANG MO NAM | monitor corporation | NLST | Oct 3, 2019 | NLST-580 |
| Exploration of deep learning-based model's lung cancer screening capabilities. | Seungwook Yang | Samsung Electronics | NLST | Oct 3, 2019 | NLST-579 |
| Image feature extraction with deep learning for mortality risk stratification on low-dose lung computed tomography | Chang-Fu Kuo | Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan | NLST | Sep 26, 2019 | NLST-572 |
| A Computer Tool for Aiding in Accurate Assessment of Indeterminate Lung Nodules | Xin Meng | International Informatics Solution Laboratory LLC | NLST | Sep 26, 2019 | NLST-571 |
| A Deep Learning Model for Improved Cancer Risk Prediction in Lung Screening Low-Dose Chest Computed Tomography | Florian Fintelmann | Massachusetts General Hospital | NLST | Sep 12, 2019 | NLST-564 |
| Lung Cancer diagnosis from radiology imaging | Babu Arunachalam | Xen.ai | NLST | Sep 11, 2019 | NLST-568 |
| Predicting lung cancer recurrence with machine learning | Flavio Calmon | Harvard University | NLST | Sep 10, 2019 | NLST-567 |
| Cost-effectiveness of low dose CT scan screening for lung cancer in New Zealand | Peter Sandiford | Waitemata District Health Board | NLST | Sep 9, 2019 | NLST-566 |
| Predicting Progression of Lung Lesions on CT scans | Sendhil Mullainathan | University of Chicago | NLST | Sep 6, 2019 | NLST-560 |
| Integrative analysis to predict lung cancer patient outcome using NLST dataset | Guanghua Xiao | UT Southwestern Medical Center | NLST | Sep 5, 2019 | NLST-562 |
| PRE-THERAPY LUNG CANCER PROGNOSTIC PREDICTION IN IMAGES | Stelmo Magalhaes Barros Neto | Universidade Federal do Maranhão | NLST | Sep 5, 2019 | NLST-558 |