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Updated: Oct 14, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Follow-up Interactive Long-Term Expert Ranking (FILTER): a crowdsourcing platform to adjudicate risk for survivorship
Alex C Cheng1, Li Wen2, Yanwei Li3
1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Objectives:
To develop an online crowdsourcing platform where oncologists and other survivorship experts can adjudicate risk for complications in follow-up.
Materials And Methods:
This platform, called Follow-up Interactive Long-Term Expert Ranking (FILTER), prompts participants to adjudicate risk between each of a series of pairs of synthetic cases. The Elo ranking algorithm is used to assign relative risk to each synthetic case.
Results:
The FILTER application is currently live and implemented as a web application deployed on the cloud.
Discussion:
While guidelines for following cancer survivors exist, refinement of survivorship care based on risk for complications after active treatment could improve both allocation of resources and individual outcomes in long-term follow-up.
Conclusion:
FILTER provides a means for a large number of experts to adjudicate risk for survivorship complications with a low barrier of entry.
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