Machine-learning-based recurrence prediction in lung cancer

Principal Investigator

Name
Pawel Badura

Degrees
Ph.D., D.Sc.

Institution
Silesian University of Technology

Position Title
Associate Professor

Email
pawel.badura@polsl.pl

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-916

Initial CDAS Request Approval
May 23, 2022

Title
Machine-learning-based recurrence prediction in lung cancer

Summary
The project is related to the analysis of volumetric computed tomography images and the application of machine learning techniques to predict clinical outcomes. The main goals are to combine radiomics tumor features with pathology and clinical patient metadata to predict recurrence and identify correlative radiomics and pathomics tumor features.

Aims

- to perform segmentation of lung nodules in LDCT,
- to explore segmented data for radiomics features,
- to combine microscopic and radiomics tumor features,
- to design machine learning tools for recurrence prediction
- to validate correlative radiomics and pathomics tumor features using external datasets.

Collaborators

Dr. Arkadiusz Gertych, Ph.D., Department of Surgery, Cedars Sinai Medical Center, Los Angeles