[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] Predicting kidney graft survival using machine learning methods: prediction model development and feature significance analysis study
Background Kidney transplantation is the optimal treatment for patients with end-stage renal
disease. Short-and long-term kidney graft survival is influenced by a number of donor and …
disease. Short-and long-term kidney graft survival is influenced by a number of donor and …
[HTML][HTML] Performance comparison of deep learning autoencoders for cancer subtype detection using multi-omics data
Simple Summary Here, we compared the performance of four different autoencoders:(a)
vanilla,(b) sparse,(c) denoising, and (d) variational for subtype detection on four cancer …
vanilla,(b) sparse,(c) denoising, and (d) variational for subtype detection on four cancer …
[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 …
[HTML][HTML] Toward advancing long-term outcomes of kidney transplantation with artificial intelligence
R Castillo-Astorga, CG Sotomayor - Transplantology, 2021 - mdpi.com
After decades of pioneering advances and improvements, kidney transplantation is now the
renal replacement therapy of choice for most patients with end-stage kidney disease …
renal replacement therapy of choice for most patients with end-stage kidney disease …
[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 …