[HTML][HTML] Recent advances and clinical outcomes of kidney transplantation
Recent advances in surgical, immunosuppressive and monitoring protocols have led to the
significant improvement of overall one-year kidney allograft outcomes. Nonetheless, there …
significant improvement of overall one-year kidney allograft outcomes. Nonetheless, there …
[HTML][HTML] On the reliability of machine learning models for survival analysis when cure is a possibility
A Ezquerro, B Cancela, A López-Cheda - Mathematics, 2023 - mdpi.com
In classical survival analysis, it is assumed that all the individuals will experience the event
of interest. However, if there is a proportion of subjects who will never experience the event …
of interest. However, if there is a proportion of subjects who will never experience the event …
FGCNSurv: dually fused graph convolutional network for multi-omics survival prediction
G Wen, L Li - Bioinformatics, 2023 - academic.oup.com
Motivation Survival analysis is an important tool for modeling time-to-event data, eg to
predict the survival time of patient after a cancer diagnosis or a certain treatment. While deep …
predict the survival time of patient after a cancer diagnosis or a certain treatment. While deep …
[HTML][HTML] Artificial intelligence-based prognostic model for urologic cancers: a SEER-based study
Simple Summary We describe a risk profile reconstruction model for cancer-specific survival
estimation for continuous time points after urologic cancer diagnosis. We used artificial …
estimation for continuous time points after urologic cancer diagnosis. We used artificial …
[图书][B] Machine Learning Methods for Precision Medicine
PG Ginestet - 2022 - search.proquest.com
In precision medicine, predicting the risk of an event during a specific period may help, for
example, to identify patients that need early preventive treatment. Modern machine learning …
example, to identify patients that need early preventive treatment. Modern machine learning …