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Explainable Machine Learning for Personalized Decision-Making in Prostate Cancer

Principal Investigator

Name
Krithika Suresh

Degrees
PhD

Institution
University of Colorado

Position Title
Assistant Professor

Email
krithika.suresh@cuanschutz.edu

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCO-726

Initial CDAS Request Approval
Jan 28, 2021

Title
Explainable Machine Learning for Personalized Decision-Making in Prostate Cancer

Summary
Machine learning algorithms have been shown to have superior predictive performance in comparison to traditional statistical models. However, they are often criticized because they lack interpretability. In this project, we propose using PLCO prostate cancer data to compare the predictive performance of various survival machine learning algorithms. We will then develop and demonstrate the use of a model-agnostic explainer for survival black-box models using PLCO data.

Aims

- Aim 1: Develop a model-agnostic explainer for survival black-box prediction models
- Aim 2: Demonstrate the use of the explainer tools for predicting prostate-cancer specific survival using PLCO data

Collaborators

Debashis Ghosh, University of Colorado
Carsten Goerg, University of Colorado
Cameron Severn, University of Colorado