Development and validation of a candidate selection model for lung cancer screening using low-dose CT
Principal Investigator
Name
Hyungjin Kim
Degrees
M.D., Ph.D.
Institution
Seoul National University Hospital
Position Title
Clinical assistant professor
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-492
Initial CDAS Request Approval
Jul 11, 2019
Title
Development and validation of a candidate selection model for lung cancer screening using low-dose CT
Summary
We aim to develop a candidate selection model for low-dose CT screening. Machine learning algorithms using clinical variables and/or images (chest radiographs) will be used for modeling, and the models will be compared with the pre-established models (Bach, Spitz, Hoggart, PLCOm2012, Pittsburgh, and so on). Updating and revising the pre-established models will be also performed. PLCO data will be used for either model development or validation.
Aims
The purpose of our study is to develop and validate a risk prediction model for selection of lung cancer screening candidates.
Collaborators
Jin Mo Goo, Seoul National University College of Medicine, Korea
Hyae Young Kim, National Cancer Center, Korea
Yeol Kim, National Cancer Center, Korea
Chang Min Park, Seoul National University Hospital, Korea