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Principal Investigator
University of south Florida
Position Title
Doctoral Student
About this CDAS Project
PLCO (Learn more about this study)
Project ID
Initial CDAS Request Approval
Oct 22, 2020
Statistical Modelling on Pancreatic Cancer
We want to utilize deep learning and advanced statistical methodologies to try to identify the significant risk factors and their corresponding interactions that contribute to pancreatic cancer. In addition, we would like to identify the percentage of the contribution of the individual risk factors and their significant interaction with the response. We also like to study the subject cancer with respect to the different treatments that are available using the concept of Cox PH method, among others as a criterion of the effect of each of the different treatments that cause the deaths of different individuals.

1. We want to find the significant risk factors along with significant interactions that affect the healthy cells of the pancreas or growing the cancerous tumor.
2. We want to build a statistical model that predicts the survival time of patients(male & female, different races) and cancerous tumors which is a function of several risk factors with a high degree of accuracy.
3. We would rank the individual risk factors and significant interactions according to the percentage of contribution to the response.
4. We want to perform a response surface analysis to find out the optimum values of the risk factors that will minimize the tumor size and maximize the survival time.
5. We would also like to perform survival analysis with the data with the proper justification of the model assumptions.


1. Aditya Chakraborty (Doctoral Candidate)
2. Dr. Chris P. Tsokos (Distinguished University Professor)