| 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 |
| Trustworthy Deep Learning Models for Calcification Assessment in Radiotherapy CT using NLST Data |
Ivana Isgum |
Amsterdam University Medical Center |
NLST |
Dec 4, 2024 |
NLST-1362 |
| 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 |
| Chest CT Radiomics and Outcomes |
Sadeer Al-Kindi |
Houston Methodist Research Institute |
NLST |
Nov 21, 2024 |
NLST-1359 |
| 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 |
| 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 |
| 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 |
| Framework for quantifying the effects of screening interventions using intermediate trial outcomes |
Vichithranie Madurasinghe |
University of Warwick |
NLST |
Oct 21, 2024 |
NLST-1344 |
| Correlation of clinical information with imaging values gained from chest CTs analyzed with deep learning algorithm |
Johannes Hofmanninger |
contextflow |
NLST |
Oct 16, 2024 |
NLST-1339 |
| Real-Time Medical Device Performance Monitoring with CUSUM Control Chart |
Constantine Gatsonis |
Brown University |
NLST |
Oct 11, 2024 |
NLST-1331 |
| Utilization of neural networks to identify and predict future cancer growth with images |
Wenzhi Zhang |
Detroit Country Day School |
NLST |
Sep 30, 2024 |
NLST-1329 |
| Integrating Early Detection of Heart Disease with Lung Cancer Screening Powered by AI |
Morteza Naghavi |
HeartLung Corporation |
NLST |
Sep 19, 2024 |
NLST-1324 |
| Cloud-based Liquid-biopsy and Radiomics Platform for the Cancer Research Data Commons |
Chun-Chi Liu |
EarlyDiagnostics |
NLST |
Sep 19, 2024 |
NLST-1323 |
| Comprehensive Tissue characterization with deep learning models utilizing NLST data for chest CT analysis |
Damini Dey |
APQ Health Inc |
NLST |
Sep 19, 2024 |
NLST-1322 |
