Enhancing post-kidney transplant prognostication: an interpretable machine learning approach for longitudinal outcome prediction
Abstract Kidney transplantation offers life-extending treatment for patients with end-stage renal disease, yet long-term risks of graft loss and death persist. Traditional prediction models using only baseline data often fail to capture patients’ evolving health status post-transplant. In this study...
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| Автори: | , , , , , , , , , , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Nature Portfolio
2025-11-01
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| Серія: | npj Digital Medicine |
| Онлайн доступ: | https://doi.org/10.1038/s41746-025-02049-4 |
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