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.

Data mining for NLST

Principal Investigator
Name
Rong Chen
Degrees
PhD
Institution
University of Maryland, Baltimore
Position Title
Assistant Professor
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-211
Initial CDAS Request Approval
Apr 19, 2016
Title
Data mining for NLST
Summary
In this project, we will use machine learning algorithms to analyze the cancer datasets, and create descriptive and predictive models. This may lead to new cancer biomarkers which can be used for personalized medicine. Our hypothesis is that machine learning is able to identify cancer biomarkers for precision medicine. Our lab have developed novel machine learning methods to analyze high-dimensional heterogeneous data. We will apply these algorithms to the cancer dataset; and compare them with standard machine learning methods.
Aims

Our lab have developed novel machine learning methods to analyze high-dimensional heterogeneous data. We will apply these algorithms to the cancer dataset; and compare them with standard machine learning methods.

Collaborators

Erika Nixon, University of Maryland School of Medicine, enixon.umm@gmail.com
Edward Herskovits, University of Maryland School of Medicine, ehh@ieee.org