Machine Learning Application of Cancer Data Analysis

Principal Investigator

Name
Mochen Li

Degrees
M.S.

Institution
Purdue University

Position Title
Teaching Assistant

Email
li1049@purdue.edu

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCO-552

Initial CDAS Request Approval
Nov 13, 2019

Title
Machine Learning Application of Cancer Data Analysis

Summary
With the application of different Machine Learning algorithms on the cancer database, it can improve the diagnosis of cancer and make statistical inference according to the related results. We hope that with as much different cancer databases obtained the more key risk factors or features can be estimated. Meanwhile, with applying machine learning and data mining methods we hope that people can analyze cancer research from a data perspective.

Aims

With different database, train different machine learning model and test the performance of corresponding models.
With different machine learning algorithms, find out the key features or key factors and make related reference with the database.
Improve the model performance and computational cost with optimization of corresponding machine learning models.
Solve the potential challenges in data analysis perspective, such as curse of high-dimensionality, noisy features.

Collaborators

Raji Sundararajan, Professor, Purdue University
Haiyan Zhang, Professor, Purdue University
Frederick Berry, Professor, Purdue University
Suranjan Panigrahi, Professor, Purdue University
Gaurav Nanda, Assistant Professor of Practice, Purdue University