Detecting Lung Cancer by Applying SOTA Deep Learning Models to Chest X-Ray Images
Principal Investigator
Name
QINGZHONG LIU
Degrees
Ph.D.
Institution
Sam Houston State University
Position Title
Full Professor
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCOI-1024
Initial CDAS Request Approval
Aug 22, 2022
Title
Detecting Lung Cancer by Applying SOTA Deep Learning Models to Chest X-Ray Images
Summary
In this study, we aim to investigate the detection performance by applying SOTA deep learning models to detecting lung cancer chest X-ray images, which may be helpful for early and convenient diagnosis of lung cancer.
We will first examine the performance of SOTA deep learning models to chest X-Ray images and then transfer the learning to other types of cancer data, and see if the latest AI techniques and models may be used for the diagnosis of the cancers.
We will first examine the performance of SOTA deep learning models to chest X-Ray images and then transfer the learning to other types of cancer data, and see if the latest AI techniques and models may be used for the diagnosis of the cancers.
Aims
Convenient diagnosis of lung cancer by using chest X-ray images with deep learning models
Collaborators
Zhongxue Chen, Professor, Biostatistics, Indiana University at Bloomington