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
nutating@gmail.com

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