Research on CT Influence Omics Method of Lung Cancer Based on Deep Transfer Learning |
Xianwei Zhao |
NPIC |
NLST |
Jul 3, 2023 |
NLST-1091 |
Methodologies for modeling clinical performance and utilities of a cancer screening test using NLST trial as an example |
James Dai |
GRAIL LLC |
NLST |
Jul 3, 2023 |
NLST-1090 |
Time to benefit for lung cancer screening from low-dose computed tomography |
Tao Chen |
Xi'an Jiaotong University |
NLST |
Jun 26, 2023 |
NLST-1089 |
Improving lung cancer risk prediction with artificial intelligence |
Chiara Paganelli |
Politecnico di Milano |
NLST |
Jun 15, 2023 |
NLST-1087 |
Development of a Nodule Risk Calculator using NLST Data |
Christopher Towe |
University Hospitals |
NLST |
Jun 15, 2023 |
NLST-1086 |
Lung Cancer Risk Research |
Chao Lang |
Qingdao Central Hospital |
NLST |
Jun 7, 2023 |
NLST-1085 |
Explainable multi-label prediction of respiratory conditions in CTs with multi-task Dirichlet-prior VAE |
Rachael Harkness |
University of Leeds |
NLST |
Jun 6, 2023 |
NLST-1084 |
Development and validation of a report generation model for the low-dose chest CT scans |
Hyungjin Kim |
Seoul National University Hospital |
NLST |
Jun 2, 2023 |
NLST-1081 |
Survival Analysis based on WSI images |
Ruofan Zhang |
Institute of Automation, CAS |
NLST |
Jun 2, 2023 |
NLST-1080 |
Prediction of pulmonary nodular malignant wind and its progression based on axial attention and lung CT |
lehua yu |
Hunan University Of Science And Technology |
NLST |
Jun 2, 2023 |
NLST-1069 |
Multimodal AI Algorithms for Diagnosis and Prognosis in Lung Cancer |
Daniel Rückert |
Technical University of Munich (TUM) |
NLST |
Jun 2, 2023 |
NLST-1075 |
Personalizing screening intervals for lung cancer screening using artificial intelligence |
Scott Adams |
University of Saskatchewan |
NLST |
May 30, 2023 |
NLST-1064 |
Exploring the generalization ability of chest XRay and CT pathology detection algorithms |
Bogdan Bercean |
S.C. Mindfully Technologies S.R.L. |
NLST |
May 30, 2023 |
NLST-1063 |
Development and validation of a CT-based prognostication model for diffuse lung parenchymal diseases |
Hyungjin Kim |
Seoul National University Hospital |
NLST |
May 30, 2023 |
NLST-1061 |
Extended follow-up NLST data to support provision of biosample data to requesters |
Ilana Gareen |
Brown University |
NLST |
May 30, 2023 |
NLST-1062 |
Lung Pathology image for ML |
Zheling Tan |
Shanghai Jiao Tong University |
NLST |
May 30, 2023 |
NLST-1065 |
Image quality assessment of digitized chest X ray images and feature characterization of "Chest X-ray Age" |
Tomoki Nakamizo |
Radiation Effects Research Foundation |
NLST |
May 30, 2023 |
NLST-1071 |
Cohort CT image features and knowledge-driven lung nodule risk assessment |
Xiao Yang |
Fuzhou University |
NLST |
May 30, 2023 |
NLST-1072 |
Develop a ChatGPT-style system for CT scan analysis |
Neet Patel |
University of California San Diego |
NLST |
May 30, 2023 |
NLST-1073 |
Evaluate Artera’s Deep Learning clinical-histologic system as a prognostic classifier for lung cancer patients |
Erin Stewart |
Artera Inc |
NLST |
May 30, 2023 |
NLST-1060 |