Skip to Main Content

COVID-19 is an emerging, rapidly evolving situation.

What people with cancer should know: https://www.cancer.gov/coronavirus

Get the latest public health information from CDC: https://www.coronavirus.gov

Get the latest research information from NIH: https://www.nih.gov/coronavirus

Principal Investigator
Name
Shazia Akbar
Degrees
Ph.D.
Institution
Altis Labs
Position Title
Machine Learning Engineer
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-588
Initial CDAS Request Approval
Oct 24, 2019
Title
Lung cancer imaging biomarker development on computed tomography using artificial intelligence
Summary
Altis Labs and UHN are collaborating to develop and validate novel lung cancer imaging biomarkers using deep learning. This project will entail labeling the data to develop detection, segmentation, and classification algorithms. We will explore the potential clinical utility when incorporating algorithms into physician workflow. Our goal is to develop robust algorithms that can be applied in clinical settings to improve patient care and outcomes.
Aims

- develop state-of-the-art nodule detection and classification algorithms
- test algorithms' utility on screening, diagnostic, and staging workflows

Collaborators

Joint Department of Medical Imaging and Quantitative Imaging for Personalized Cancer Medicine, UHN
Research and Development, Altis Labs