External Validation of an Intelligent Diagnosis Model for LDCT.
Principal Investigator
Name
Zhangyan Lyu
Degrees
Ph.D.
Institution
Tianjin Medical University Cancer Institute and Hospital
Position Title
Research Associate
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-880
Initial CDAS Request Approval
Feb 2, 2022
Title
External Validation of an Intelligent Diagnosis Model for LDCT.
Summary
Lung cancer has become a huge burden for human health. Population-based community screening to identify pulmonary nodules may be the best way for early diagnosis and early treatment of lung cancer. Low-dose CT (LDCT) examination is currently an internationally recognized method for lung cancer screening, but the false positive rate of LDCT is sitll high. Artificial intelligence technology can improve the recognition of medical images, and thus provide new ideas for lung nodule discrimination and lung cancer diagnosis. We proposed to validate the intelligent diagnosis model for LDCT which we developed utilizing Tianjin Database. The results can be applied to community lung cancer screening in China to enhancing the efficiency of early diagnosis and early treatment for lung cancer.
Aims
To evaluate the accuracy of the Intelligent Diagnosis Model for LDCT and the effectiveness of AI-assisted LDCT in lung cancer screening in China.
Collaborators
None.