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.

Artificial Neural Network Analysis of NLST Data for determining clusters of patient factors and CT lesion features most predictive of true positives and true negatives, false positives and false negatives

Principal Investigator
Name
John Weaver
Degrees
MD
Institution
HealthView Preventive Medical Center
Position Title
faculty radiologist
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-27
Initial CDAS Request Approval
Jul 25, 2013
Title
Artificial Neural Network Analysis of NLST Data for determining clusters of patient factors and CT lesion features most predictive of true positives and true negatives, false positives and false negatives
Summary
The NLST CT data will be subjected to Artificial Neural Network Analysis to try to determine which patient factors and CT lesion features are most useful in identifying malignant lesions and benign lesions to aid in construction of useful algorithms for CT readers to use in daily work.
Aims

The identification of patient factors and CT lesion features most useful for CT readers to use in daily work.

Collaborators

none