| Diagnosing COVID-19 from deep learning trained on CT scans |
Jean-Remi King |
CNRS |
NLST |
Mar 17, 2020 |
NLST-650 |
| Lung tumor early detection and prognosis with machine learning approach |
Tengfei Li |
University of North Carolina at Chapel Hill |
NLST |
Mar 16, 2020 |
NLST-649 |
| Development of DCNN-based solution for lung cancer detection based on CT images. |
Noé Samaille |
IBM |
NLST |
Mar 16, 2020 |
NLST-648 |
| Autoencoder for CT images and automatic clustering of patients |
michael roberts |
Astrazeneca |
NLST |
Mar 10, 2020 |
NLST-647 |
| Similar Patient Search for Cancer Patients |
Elham Taghizadeh |
Fraunhofer MEVIS: Institute for Digital Medicine |
NLST |
Mar 10, 2020 |
NLST-645 |
| Lung Cancer Detection and Classification Using Deep Learning |
Daniel Korat |
Interdisciplinary Center Herzliya |
NLST |
Mar 3, 2020 |
NLST-643 |
| Lung cancer prognosis in CNUH |
Vi Vo Thi Tuong |
Chonnam National University |
NLST |
Feb 24, 2020 |
NLST-640 |
| Development and Investigation of Class Imbalanced Data Methods for Lung Cancer Incidence Prediction Using Clinical and Radiomics Data |
Matloob Khushi |
The University of Sydney |
NLST |
Feb 24, 2020 |
NLST-641 |
| Imaging Biomarkers for Lung Cancer Screening |
Hengyong Yu |
University of Massachusetts Lowell |
NLST |
Feb 19, 2020 |
NLST-639 |
| Evaluation of Thoracic Aortic Aneurysm Mortality with Low-Dose Computed Tomographic Screening. |
A Claire Watkins |
Stanford University |
NLST |
Feb 19, 2020 |
NLST-638 |
| Improve Lung Cancer Prediction by Training Multi-task Self-supervised Pre-training on Large Unlabeled Data |
Yi Chen |
ASUS AICS |
NLST |
Feb 19, 2020 |
NLST-637 |
| A new mathematical model for the computation of optimal cancer surveillance schedules |
Johannes Reiter |
Stanford University |
NLST |
Feb 7, 2020 |
NLST-636 |
| Developing a prognostic prediction model using Delta Radiomic Features and Clinical Information for Lung Cancer Detection |
XIAOFENG WANG |
Cleveland Clinic |
NLST |
Jan 30, 2020 |
NLST-634 |
| Comparison of National Lung Cancer Resection Outcomes to Screening Trial Outcomes |
Tyler Grenda |
Sidney Kimmel Medical College, Thomas Jefferson University |
NLST |
Jan 27, 2020 |
NLST-633 |
| Lung cancer detection using Deep Convolutional Neural Network |
Deepa P L |
Mar Baselios College of Engineering and Technology |
NLST |
Jan 27, 2020 |
NLST-632 |
| Improvement of the Accuracy in Detection of pulmonary nodules |
Wei-Ying Chen |
International Integrated Systems, Inc |
NLST |
Jan 27, 2020 |
NLST-631 |
| Studies to use extended NLST follow-up data |
Hormuzd Katki |
NCI |
NLST |
Jan 27, 2020 |
NLST-626 |
| Targeting low-dose computer tomography screening to improve lung-cancer survival: a machine learning-based post-hoc analysis of heterogeneous treatment effects in the National Lung Screening Trial |
Liangyuan Hu |
Icahn School of Medicine |
NLST |
Jan 27, 2020 |
NLST-630 |
| Data-efficient and interpretable machine learning framework for lung cancer screening |
Lei Xing |
Stanford University |
NLST |
Jan 27, 2020 |
NLST-628 |
| Development of lung cancer diagnostic artificial intelligence based on CT images |
Mate Denes |
Ulyssys Ltd. |
NLST |
Jan 10, 2020 |
NLST-627 |
