A machine learning-derived biological age model for liver grafts provides a superior assessment of aging compared to chronological age in transplantation
Abstract Liver transplantation is severely restricted by shortages of donors, yet relying on chronological age (CA) for donor selection often results in potentially viable grafts being discarded. This study developed a machine learning-based framework to predict the biological age (BA) of liver graf...
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| Asıl Yazarlar: | , , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
Nature Portfolio
2026-03-01
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| Seri Bilgileri: | Scientific Reports |
| Konular: | |
| Online Erişim: | https://doi.org/10.1038/s41598-026-45531-z |
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