Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques

Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques

Abstract Background Predicting survival of recipients after liver transplantation is regarded as one of the most important challenges in contemporary medicine. Hence, improving on current prediction models is of great interest.Nowadays, there is a strong discussion in the medical field about machine...

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Bibliografski detalji
Glavni autori: Georgios Kantidakis, Hein Putter, Carlo Lancia, Jacob de Boer, Andries E. Braat, Marta Fiocco
Format: Članak
Jezik:English
Izdano: BMC 2020-11-01
Serija:BMC Medical Research Methodology
Teme:
Random survival forest
Neural networks
Predictive performance
Risk factors
Post-transplantation
Survival analysis
Online pristup:http://link.springer.com/article/10.1186/s12874-020-01153-1

Internet

http://link.springer.com/article/10.1186/s12874-020-01153-1

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