Skip to Main Content
An official website of the United States government

Government Funding Lapse

Because of a lapse in government funding, the information on this website may not be up to date, transactions submitted via the website may not be processed, and the agency may not be able to respond to inquiries until appropriations are enacted. The NIH Clinical Center (the research hospital of NIH) is open. For more details about its operating status, please visit cc.nih.gov. Updates regarding government operating status and resumption of normal operations can be found at OPM.gov.

Prediction of Lung cancer and mortality using machine learning and deep learning

Principal Investigator

Name
Thu Cao

Degrees
MA

Institution
Columbia University Medical Center

Position Title
Data Analyst

Email
ttc2131@cumc.columbia.edu

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-609

Initial CDAS Request Approval
Nov 26, 2019

Title
Prediction of Lung cancer and mortality using machine learning and deep learning

Summary
Using radiological, histological images and clinical information from the NLST, we are aiming to develop predictive models using machine learning and deep learning techniques to automatically detect lung lesions and predict mortality.

Aims

1. Determine an effective approach for data processing for most accurate predictive model.
2. Develop an effective deep learning and machine learning model to identify lung lessons
3. Build a machine leaning model to predict mortality with high accuracy

Collaborators

B. Payne Stanifer, MD – Columbia University Medical Center