It remains unclear whether machine learning methods can accurately identify cancer driver alterations. Here, the authors compare machine learning-based approaches to other computational methods to determine their utility for annotating variants of unknown significance and identifying driver alterations in real-world cancer patient data, demonstrating superior performance.
- Thinh N. Tran
- Chris Fong
- Justin Jee
