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| Zdroj: |
Blood Weekly; 5/23/2024, p216-216, 1p |
| Abstrakt: |
A new study conducted by researchers at the University of Utah has found that artificial intelligence (AI) algorithms can improve the prediction of outcomes for live-donor kidney transplants. The study evaluated pre-transplant variables from a database of over 66,000 transplants and tested four machine learning models for discrimination and calibration. The deep Cox mixture model showed the best performance, outperforming existing prediction models. The researchers believe that this AI-based model has the potential to improve decisions for live donor selection and could be adopted to enhance the outcomes of paired exchange programs. [Extracted from the article] |
| Databáze: |
Complementary Index |
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