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