Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method

Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method

Summary: Background: Current lung cancer screening guidelines use either mean diameter, volume, or density of the largest lung nodule on the previous CT scan or appearance of a new nodule to ascertain the timing of the next CT scan. We aimed to develop an accurate screening protocol by estimating t...

Full description

Bibliographic Details
Main Authors: Peng Huang, PhD, Cheng T Lin, MD, Yuliang Li, MS, Martin C Tammemagi, ProfPhD, Malcolm V Brock, ProfMD, Sukhinder Atkar-Khattra, BSc, Yanxun Xu, PhD, Ping Hu, ScD, John R Mayo, ProfMD, Heidi Schmidt, ProfMD, Michel Gingras, MD, Sergio Pasian, MD, Lori Stewart, MD, Scott Tsai, MD, Jean M Seely, MD, Daria Manos, MD, Paul Burrowes, MD, Rick Bhatia, MD, Ming-Sound Tsao, ProfMD, Stephen Lam, ProfMD
Format: Article
Language:English
Published: Elsevier 2019-11-01
Series:The Lancet: Digital Health
Online Access:http://www.sciencedirect.com/science/article/pii/S2589750019301591

Internet

http://www.sciencedirect.com/science/article/pii/S2589750019301591

Similar Items