A Systematic Review on Machine Learning Techniques for Survival Analysis in Cancer
Autumn O'Donnell1,2, Michael Cronin3, Shirin Moghaddam2,4,5,6
1School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland.
Cancer Medicine
|November 20, 2025
Summary
Machine learning (ML) shows improved cancer survival analysis performance. Multi-task and deep learning methods show promise, but ML implementation varies significantly across studies.
Area of Science:
- Oncology
- Biostatistics
- Computer Science
Background:
- Conventional survival analyses in cancer studies have limitations.
- Machine learning (ML) presents potential solutions but performance varies.
- Uncertainty exists regarding ML's consistent superiority over traditional methods.
Conclusions:
- Machine learning generally enhances predictive performance in cancer survival analysis.
- While promising, multi-task and deep learning methods require further investigation due to limited reporting.
- Standardization of ML methodologies and implementation is needed for reliable comparisons.
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