Approved Projects
Here you can browse the complete list of projects on CDAS whose requests for data/biospecimens were approved.
| Name | Principal Investigator | Institution | Study | Date Approved | Project ID |
|---|---|---|---|---|---|
| Lung cancer prediction using artficial neural networks | Saudagar Barde | Smt kashibai navle college of engineering | PLCO | Jan 3, 2018 | PLCO-334 |
| Deep Learning at Chest Radiography and CT: Automated Detection and Diagnosis of Cancers. | Daiju Ueda | Department of Radiology and Interventional Radiology, Graduate School of Medicine, Osaka City University | NLST | Jan 2, 2018 | NLST-384 |
| Machine learning to predict risk from chest radiographs and clinical factors | Michael Lu | The General Hospital Corporation d/b/a Massachusetts General Hospital | NLST | Dec 29, 2017 | NLST-383 |
| Influence of accelerometer calibration approach on MVPA estimates for adults | charles matthews | NCI / DCEG / Metabolic Epidemiology Branch | IDATA | Dec 28, 2017 | IDATA-19 |
| Impact of Lung Cancer Screening on Lung Cancer Mortality in COPD Patients | Juan Wisnivesky | Icahn School of Medicine at Mount Sinai | NLST | Dec 26, 2017 | NLST-380 |
| Computerized Heart and Lung Disease Detection in Low-dose CT Images | Pingkun Yan | Rensselaer Polytechnic Institute | NLST | Dec 19, 2017 | NLST-382 |
| Machine learning to predict risk from chest radiographs and clinical factors | Michael Lu | The General Hospital Corporation d/b/a Massachusetts General Hospital | PLCO | Dec 19, 2017 | PLCO-331 |
| Incidence lung cancers after negative screening rounds: A retrospective review of CT findings and outcomes | Jihang Kim | Seoul National University Bundang Hospital | NLST | Dec 11, 2017 | NLST-379 |
| detecting, marking and classifying lung cancer in CT-Scans with deep learning algorithms | Qasim Mohammad | Independent | NLST | Dec 1, 2017 | NLST-378 |
| Automatic Lung Lesion Detection and Segmentation in CT | Lin Yang | University of Florida | NLST | Nov 29, 2017 | NLST-377 |
| A simulation modeling study examining the downstream effects of follow-up schedules for screen-detected nodules | Chung Yin (Joey) Kong | Massachusetts General Hospital | PLCO | Nov 27, 2017 | PLCO-317 |
| A genome-wide association study of lifecourse weight change | Sonja Berndt | National Cancer Institute | PLCO | Nov 27, 2017 | PLCO-325 |
| Deep learning on Screening Data | Elliot Smith | Maxwell MRI | PLCO | Nov 27, 2017 | PLCO-328 |
| Towards personalized cancer treatment with deep learning | Francesco Ciompi | Radboud University Medical Center | PLCO | Nov 24, 2017 | PLCOI-323 |
| Detection/Segmentation of lung cancer and more with deep learning | Andy Song | Medipixel | NLST | Nov 17, 2017 | NLST-376 |
| Computer-aided diagnosis system for lung-related pathology | Aurélio Campilho | INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência | NLST | Nov 15, 2017 | NLST-375 |
| Lung cancer investigation based on deep learning; detection, diagnosis and prognosis prediction | Chin A Yi | Sungkyunkwan University School of Medicine | NLST | Nov 14, 2017 | NLST-366 |
| Using Artificial Intelligence for the automatic interpretation of chest CT images | Hugo Aerts | Dana-Farber Cancer Institute, Inc. | NLST | Nov 14, 2017 | NLST-374 |
| New image features for automatically discrimination of patients with/without lung cancer | Consuelo Gonzalo Martin | UNIVERSIDAD POLITECNICA DE MADRID | NLST | Nov 14, 2017 | NLST-373 |
| Simulation study as supplement to EEMS proposal 2017-0029, “Circulating Estrogens, Androgens, and Progestogens and Risk of Breast Cancer in the PLCO Cohort”. | Barry Graubard | National Cancer Institute | PLCO | Nov 10, 2017 | PLCO-326 |