| Predict site-specific and multiple cancer risk through cohort study data of NLST |
Fulan Hu |
Shenzhen University Medical School |
NLST |
Jan 13, 2025 |
NLST-1382 |
| Utilization of Deep Learning Architectures for the Automated Detection of Pulmonary tumor and Tuberculosis in Thoracic Radiographic Imaging |
Mutlu Avci |
Çukurova University |
NLST |
Jan 10, 2025 |
NLST-1380 |
| Data-driven Optimal Personalized Early Screening Strategies for Lung Cancer |
Jianjin Yue |
Sichuan University |
NLST |
Jan 6, 2025 |
NLST-1374 |
| Association Between Age and Lung Cancer: Exploring the Mediating Effects of Lobar Radiomics |
Lei Shi |
Radiology Department of Zhejiang Cancer Hospital |
NLST |
Dec 16, 2024 |
NLST-1371 |
| Evaluating whether 3D chest extrapulmonary musculature measurements improve prediction performance relative to conventional risk factors for all-cause mortality in a lung cancer screening cohort. |
Miranda Kirby |
Toronto Metropolitain University |
NLST |
Dec 16, 2024 |
NLST-1370 |
| Multimodal Deep Learning Model for Lung Cancer Detection: Optimal Fusion of Radiological and Clinical Data for Precision Medicine |
Tushar Mehta |
Parkland High School |
NLST |
Dec 16, 2024 |
NLST-1369 |
| Evaluating the Impact of Radiologist Experience and AI Integration on Lung Cancer Screening Performance: A Comparative Analysis of a Leading Dutch Radiology Center Using NLST Data |
Alex Puiu |
PRMSE-SCREENING |
NLST |
Dec 16, 2024 |
NLST-1368 |
| Multimodal and interpretable deep learning algorithm to classify lung nodules |
Luis Montuenga |
University of Navarra |
NLST |
Dec 16, 2024 |
NLST-1367 |
| A nested case-control study from NLST to evaluate a multiplex protein biomarker-based immunoassay for the early detection of bladder cancer |
Charles Rosser |
Cedars-Sinai Medical Center |
NLST |
Nov 21, 2024 |
NLST-1360 |
| Improving risk stratification for lung cancer screening using peripheral blood leukocyte DNA methylation: an investigation in the National Lung Screening Trial (NLST) |
Dominique Michaud |
Tufts University |
NLST |
Nov 19, 2024 |
NLST-1358 |
| Improved Methods for Comparing Human Radiologists to AI tools |
Ashesh Rambachan |
Massachusetts Institute of Technology |
NLST |
Nov 12, 2024 |
NLST-1357 |
| Machine Learning approach for the analysis of lung cancer data to aid the radiologists at global level |
Tiratharaj Singh |
Jaypee University of Information Technology (JUIT) |
NLST |
Nov 12, 2024 |
NLST-1355 |
| Predicting Lung Nodule Growth Using Deep Learning Methods |
gao dong chen |
Shan Dong University |
NLST |
Nov 5, 2024 |
NLST-1354 |
| Using deep learning models to infer spatial transcriptomics from H&E slides |
Eytan Ruppin |
Cancer Data Science Laboratory, NCI |
NLST |
Nov 5, 2024 |
NLST-1353 |
| Comparing the accuracy of machine learning diagnosis of lung cancer from different data modalities |
Polina Golland |
Massachusetts Institute of Technology |
NLST |
Nov 5, 2024 |
NLST-1349 |
| Radiomics-Driven Predictive Lung Cancer Models |
Patrice Essien |
George Washington University |
NLST |
Nov 5, 2024 |
NLST-1347 |
| Surrogate endpoints for cancer screening trials |
Adam Brentnall |
Queen Mary University of London |
NLST |
Nov 5, 2024 |
NLST-1345 |
| Analysis of Chest X-rays Based on Deep Learning for Health Risk Assessment |
Yu Fei Huang |
China Medical University |
NLST |
Nov 5, 2024 |
NLST-1351 |
| Quantification of Interstitial Lung Abnormalities Using Data from the National Lung Screening Trial |
Hyungjin Kim |
Seoul National University Hospital |
NLST |
Nov 5, 2024 |
NLST-1350 |
| Combined model integrating pericardial fat and tumor radiomics with clinical data to classify pulmonary nodules: A multicentric analysis |
Wenjuan Huang |
Harbin medical university cancer hospital |
NLST |
Nov 5, 2024 |
NLST-1346 |
