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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
bbnerjee@memphis.edu

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

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