[HTML][HTML] Recent advances and clinical outcomes of kidney transplantation

C Thongprayoon, P Hansrivijit, N Leeaphorn… - Journal of Clinical …, 2020 - mdpi.com
Recent advances in surgical, immunosuppressive and monitoring protocols have led to the
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

SAA Naqvi, K Tennankore, A Vinson, PC Roy… - Journal of Medical …, 2021 - jmir.org
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 …

[HTML][HTML] Performance comparison of deep learning autoencoders for cancer subtype detection using multi-omics data

EF Franco, P Rana, A Cruz, VV Calderon, V Azevedo… - Cancers, 2021 - mdpi.com
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 …

[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 …

[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 …

[HTML][HTML] Artificial intelligence-based prognostic model for urologic cancers: a SEER-based study

O Eminaga, E Shkolyar, B Breil, A Semjonow… - Cancers, 2022 - mdpi.com
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 …