Early Detection and Personalized Treatment of Colon Cancer: Integrating Genetic, Demographic, and Lifestyle Data
Principal Investigator
Name
JULIET KURUVILLA
Degrees
M.S.
Institution
HOWARD UNIVERSITY
Position Title
Data Science program - Research
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-1460
Initial CDAS Request Approval
Jan 26, 2024
Title
Early Detection and Personalized Treatment of Colon Cancer: Integrating Genetic, Demographic, and Lifestyle Data
Summary
How can machine learning techniques be leveraged to predict and classify different stages of colon cancer based on diverse patient data, including genetic markers, demographic information, and lifestyle factors, in order to enhance early detection and personalized treatment strategies?
Aims
I am currently enrolled in the Masters of Applied Data Science program at Howard University. I am looking for a perfect PLCO dataset for use in the Applied Machine Learning course project under the guidance of Dr. Ameyaw (email address: edmundessah.ameyaw@howard.edu).
Collaborators
Juliet Kuruvilla
Email: julietkuruvilla@gmail.com (personal), juliet.kuruvilla1@bison.howard.edu (academic)