| Development of Deep Learning algortihms for the automated Calcium Scoring identification from radiological studies |
Fernando Martin |
WellSpan Health |
NLST |
Apr 4, 2022 |
NLST-905 |
| Lung Nodule Detection |
Asma Alkhaldi |
Saudi Data and Artificial Intelligence Authority (SDAIA) |
NLST |
Mar 30, 2022 |
NLST-896 |
| X-ray Dissectography Improves Lung Nodule Detection |
Chuang Niu |
Rensselaer Polytechnic Institute |
NLST |
Mar 30, 2022 |
NLST-900 |
| Validation of a survival prediction model in participants with lung cancer |
Hyungjin Kim |
Seoul National University Hospital |
NLST |
Mar 24, 2022 |
NLST-899 |
| Emphysema quantification using lung cancer screening CT scans: diagnostic and prognostic value |
Hyungjin Kim |
Seoul National University Hospital |
NLST |
Mar 24, 2022 |
NLST-898 |
| Deep based cancer/nodule detection project |
WenJia Song |
University of Queensland |
NLST |
Mar 22, 2022 |
NLST-894 |
| Identification of actionable lung nodules with low-dose computed tomography screening: Characterizing the effects on observer performance of a personalized Artificial Intelligence feedback |
Jessica Sieren |
University of Iowa |
NLST |
Mar 21, 2022 |
NLST-895 |
| Apply new statistical methods to assess screening efficacy in NLST trial addressing overdiagnosis |
ying huang |
Fred Hutchinson Cancer Research Center |
NLST |
Mar 7, 2022 |
NLST-891 |
| Thyroid carcinoma relation with ovaries using Machine Learning Techniques |
Geetanjali Rave |
Ramaiah Institute of Technology |
NLST |
Mar 2, 2022 |
NLST-890 |
| 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 |
