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Survival Curves for Hierarchical Data

Principal Investigator
Name
Ali Parsaee
Degrees
Masters
Institution
University of Alberta
Position Title
Student
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-1241
Initial CDAS Request Approval
May 30, 2023
Title
Survival Curves for Hierarchical Data
Summary
In the field of survival analysis we wish to generate individualized survival curves to give a probability of an event (such as death) occurring for any one patient at a given time. There are many strong machine learning methods that build effective models for this task. However assume your data is on Lung cancer and one of the features in the dataset describes the state of cancer the patient is in. If a patient comes in with stage 4 lung cancer, do you build the survival curve based only on the subset of the dataset dealing with stage 4 lung cancer? The whole dataset? A mix of the two?
Aims

-Generate the most effective individualized survival curve for a coming patient
-Describe with theory and experiment what subset of the dataset to take

Collaborators

Professor Russ Greiner, University of Alberta