Two-sided conformalized survival analysis

TL;DR

This paper introduces a conformal prediction method for survival analysis that creates reliable two-sided or one-sided prediction intervals with finite-sample guarantees, applicable even with censored data.

Contribution

It proposes a novel conformal prediction procedure tailored for survival analysis, providing finite-sample coverage guarantees without distributional assumptions.

Findings

Method achieves valid coverage on synthetic data

Effective in real-world survival datasets

Provides both two-sided and one-sided intervals

Abstract

This paper presents a conformal prediction procedure to generate two-sided or one-sided prediction intervals for survival times in the presence of right censoring. Specifically, the method provides two-sided predictive bounds for individuals deemed sufficiently similar to the uncensored population, while returning a lower predictive bound for others. The prediction intervals offer finite-sample coverage guarantees, requiring no distributional assumptions other than the sampled data points are independent and identically distributed. The performance and validity of the procedure is evaluated on both synthetic and real-world datasets.