Using Explainable Machine Learning to Explore the Impact of Synoptic Reporting on Prostate Cancer
Machine learning (ML) models have proven to be an attractive alternative to traditional statistical methods in oncology. However, they are often regarded as <i>black boxes</i>, hindering their adoption for answering real-life clinical questions. In this paper, we show a practical applica...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/15/2/49 |