Predicting Cancer diagnosis based on preliminary screenings
Principal Investigator
Name
Jonathan Mendoza
Degrees
Associates
Institution
Independent
Position Title
Student
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-532
Initial CDAS Request Approval
Oct 24, 2019
Title
Predicting Cancer diagnosis based on preliminary screenings
Summary
I want to see if it is possible to predict the likely-hood of a cancer diagnosis based on collected data from screenings and other diagnostics performed.
I will be using machine learning algorithms in an attempt to predict cancer diagnosis based on the features available in PLCO. I am currently working with one of the SEER datasets and my algorithms have been able to predict, with a fair amount of precision, the length of time a person might live after multiple cancer diagnosis. I would like the bring some of that predictive power to these datasets and see if it is possible to predict the likelihood of a cancer diagnosis. If successful, I would hope to continue my research on further datasets.
I will be using machine learning algorithms in an attempt to predict cancer diagnosis based on the features available in PLCO. I am currently working with one of the SEER datasets and my algorithms have been able to predict, with a fair amount of precision, the length of time a person might live after multiple cancer diagnosis. I would like the bring some of that predictive power to these datasets and see if it is possible to predict the likelihood of a cancer diagnosis. If successful, I would hope to continue my research on further datasets.
Aims
-Predict cancer diagnosis with a better than baseline probability
Collaborators
n/a