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Impact of a Commercial Deep learning-based Algorithm in Advancing Lung Cancer Detection on the Screening with Chest Radiographs.

Principal Investigator

Name
JU NAM

Degrees
M.D.

Institution
Seoul National University Hospital

Position Title
Clinical Fellow

Email
dyuing89@gmail.com

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCO-489

Initial CDAS Request Approval
Jul 11, 2019

Title
Impact of a Commercial Deep learning-based Algorithm in Advancing Lung Cancer Detection on the Screening with Chest Radiographs.

Summary
Chest radiographs have been showing poor results in lung cancer screening. However, deep learning based detection algorithms have been reported to exhibit high performance in detecting malignant lung nodules, and they may enhance the feasibility of chest radiographs in lung cancer screening.
We would like to investigate if a commercially used deep learning-based lung cancer detection algorithm on chest radiographs can advance the lung cancer detection on screening setting. For the patients diagnosed as lung cancer during the screening, we would like to examine the last chest radiograph which was called negative on the formal report. For some of those in which the nodule was visible on the retrospective focused review, so-called missed cancer lesions, we would like to apply a commercially used deep learning based detection algorithm and see how the algorithm work on those images.

Aims

To investigate if deep learning based detection algorithm may advance lung cancer detection on the screening with chest radiography.

Collaborators

Chang Min Park, Seoul National University Hospital.