Risk prediction model for lung cancer incidence using Machine Learning Algorithms
Principal Investigator
Name
Ning Li
Degrees
Ph.D candidate in Biostatistics
Institution
Peking Union Medical College
Position Title
Ph.D candidate
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-627
Initial CDAS Request Approval
May 20, 2020
Title
Risk prediction model for lung cancer incidence using Machine Learning Algorithms
Summary
I am doing my final year project in biostatistics which involves building a risk prediction model for lung cancer using different statistics methods and I need a dataset which contains the risk factors associated with this type of cancer. I plan to build a risk model for lung cancer using PLCO data which can assist high-quality decision-making, help to stratify high risk individuals identified accurately and this model can be ease of use and interpretation.
Aims
The objectives:
1. Fine an accurate probability of combining different risk factors to lung cancer for each individual.
2. Idientify and stratify high risk population.
3. Using the NLST data to compare the discrepancy power with other risk models.
4. Compute the score of attributable risk percent according to the risk model
Collaborators
On this project I am collaborating with my supervisor Jingmei Jiang