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.

Use of biometric data in pancreatic cancer prediction

Principal Investigator
Name
Bonny Banerjee
Degrees
Ph.D.
Institution
University of Memphis
Position Title
Associate Professor
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-469
Initial CDAS Request Approval
Apr 10, 2019
Title
Use of biometric data in pancreatic cancer prediction
Summary
The purpose of our work is to find a pattern in the biometric data if certain dietary habits, family hitory of diabetes/stroke etc contribute more towards pancreatic cancer. We would like to develop a model in real-time that can automatically predict based on subject's data if he's susceptible to pancreatic cancer. We are developing a mathematical model based on machine learning to take as input all the biometric data of the test subjects and the known output(that is they contracted pancreatic cancer within period T, or if they didnot contract any form of cancer in period T). If the subject contracted pancreatic cancer, the model will also predict if he will survive or if his maximum life expectancy. So the time till the patient died from pancreatic cancer should also be contained in the dataset.
Aims

Development of a mathematical model for early prediction of pancreatic cancer.

Determine a pattern from the biometric data if certain set of subjects are more prone to develop pancreatic cancer than others.

Collaborators

NA

Related Publications