Skip to Main Content

An official website of the United States government

Government Funding Lapse

Because of a lapse in government funding, the information on this website may not be up to date, transactions submitted via the website may not be processed, and the agency may not be able to respond to inquiries until appropriations are enacted. The NIH Clinical Center (the research hospital of NIH) is open. For more details about its operating status, please visit  cc.nih.gov. Updates regarding government operating status and resumption of normal operations can be found at OPM.gov.

Prediction of abnormalities in Chest X-Rays with Machine learning techniques

Principal Investigator
Name
Sasa Grbic
Degrees
Ph.D.
Institution
Siemens Medical Solutions
Position Title
Staff Scientist
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-311
Initial CDAS Request Approval
Oct 10, 2017
Title
Prediction of abnormalities in Chest X-Rays with Machine learning techniques
Summary
Explore possibility to predict abnormality in Chest X-Ray (collected within PLCO data base) with state of the art deep learning technologies.
Aims

Aim1: Building and testing existing deep neural networks to predict normal/vs abnormal scans based on solely Chest X-Rays (validation on accuracy, specificity and sensitivity)
Aim 2: Building and testing existing deep neural networks to predict abnormality labels based on solely Chest X-Rays (validation on accuracy, specificity and sensitivity)

Collaborators

Sasa Grbic
Dominik Neumann
Daguang Xu
Sebastian Guendel
Puneet Sharma
Yefeng Zheng