| Deep Learning for Prediction of Progression and Overall Survival of Lung Cancer using CT Examinations |
Brian Huang |
University of Pennsylvania |
NLST |
Aug 18, 2020 |
NLST-705 |
| Development of Ultra High Resolution CT for Differential Diagnosis of Lung Nodules found using Low Dose CT |
Rasika Rajapakshe |
BC Cancer Agency Sindi Ahluwalia Hawkins Centre for the Southern Interior |
NLST |
Aug 18, 2020 |
NLST-703 |
| Development of deep-learning software for the detection, classification, and malignancy risk assessment of lung nodules on LDCT |
Kenneth Tang |
AIRdx |
NLST |
Aug 18, 2020 |
NLST-702 |
| Subgroup Identification based on Lung Cancer Risk Prediction Model |
Jon Steingrimsson |
Brown University |
NLST |
Aug 5, 2020 |
NLST-701 |
| Blood-based biomarkers as a complement to CT screening for lung cancer |
Edwin Ostrin |
University of Texas MD Anderson Cancer Center |
NLST |
Jul 29, 2020 |
NLST-698 |
| Deep Learning Reconstruction of Chest CT Volumes from Single or Multi View Chest Radiographs |
Nadav Shapira |
University of Pennsylvania |
NLST |
Jul 24, 2020 |
NLST-697 |
| DeepCoronaScan |
Christophe Zimmer |
Institut Pasteur Paris |
NLST |
Jul 21, 2020 |
NLST-696 |
| Effect of lung morphology on particle deposition in the airways |
Uduak George |
San Diego State University |
NLST |
Jul 17, 2020 |
NLST-694 |
| Prognostic implication of thoracic muscle and visceral fat in chest CT image in lung cancer screening participants |
Soon Ho Yoon |
Seoul National University Hospital |
NLST |
Jul 17, 2020 |
NLST-695 |
| Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images |
Mohammad Soltanieh-ha |
Boston University |
NLST |
Jul 13, 2020 |
NLST-692 |
| Deep learning model using multi-modal data for lung cancer survival prediction |
yingying zhu |
University of Texas, Arlington |
NLST |
Jul 7, 2020 |
NLST-684 |
| Actionable Intelligence Research for Early Lung Cancer Detection |
Jia Wu |
MD Anderson Cancer Center |
NLST |
Jul 7, 2020 |
NLST-690 |
| Lung Cancer Nodule Detection Using Algorithm. |
MUHAMMAD UMAIR |
NED UNIVERSITY |
NLST |
Jul 7, 2020 |
NLST-688 |
| Development of CNN-based model in predicting patients outcomes |
Shaunagh McDermott |
Massachusetts General Hospital |
NLST |
Jun 30, 2020 |
NLST-686 |
| Smart Radiology: an algorithm to predict the risk index of lung nodules in LDCT. |
Marcelo Oliveira |
Universidade Federal de Alagoas (UFAL) |
NLST |
Jun 29, 2020 |
NLST-685 |
| Varying preferences for predictive information among patients at risk for lung cancer |
Gary Weissman |
University of Pennsylvania Perelman School of Medicine |
NLST |
Jun 26, 2020 |
NLST-682 |
| Development and evaluation of deep-learning algorithm for the classification of lung nodules detected on CT-Scan |
Cecile Dupont |
MD Start |
NLST |
Jun 26, 2020 |
NLST-683 |
| Deep learning mortality prediction in NLST data |
Joseph Jacob |
University College London |
NLST |
Jun 26, 2020 |
NLST-681 |
| Applications of Deep Learning for the Automatic or Semi-automatic Detection of Lung Abnormalities |
Suryadipto Sarkar |
Arizona State University |
NLST |
Jun 22, 2020 |
NLST-679 |
| Comparison of radiologist recommended follow-up with procedures received by study participants following screening with LDCT |
Nana Boame |
Brown University |
NLST |
Jun 22, 2020 |
NLST-680 |
