Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models
The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretable methods to predict both graft failure and patien...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2024
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