AI Enhanced Triage in Lung Cancer Screening
Principal Investigator
Name
Gerardo Hermosillo Valadez
Degrees
Ph.D.
Institution
Siemens Medical Solutions USA
Position Title
Research and Technology Manager
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1314
Initial CDAS Request Approval
Sep 5, 2024
Title
AI Enhanced Triage in Lung Cancer Screening
Summary
Evaluate existing AI technologies for their accuracy in detecting, measuring, and classifying pulmonary nodules, as well as estimating malignancy risk and identifying incidental findings. Explore methods to prioritize allocation of resources to significant findings based on patient history and priors.
Aims
1 Quantify False Positives and Malignancy Risk Scores: Determine the frequency and types of false positives and assess the accuracy of AI-based malignancy risk scores.
2 Evaluate AI-Driven Nodule Measurement and Tracking: Measure the accuracy and reliability of AI systems in the automatic measurement and longitudinal tracking of pulmonary nodules.
3 Improve Triage Systems for Non-Actionable Patients: Assess the negative predictive value and specificity of AI-based triage systems designed to rule out non-actionable patients.
Collaborators
Abdishektaei, Arya
Farhand, Sepehr
Yerebakan, Halid
Guo, Xueqi
Wolf, Matthias
Peng, Zhigang
Shinagawa, Yoshihisa
Ranganath, Mahesh,
Iyer, Kritika
Allen-Raffl, Simon