Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Development, External Validation, and Deployment of RFAN-ML: A Machine Learning Model to Estimate Renal Function After Nephrectomy
0
Zitationen
12
Autoren
2025
Jahr
Abstract
We developed and externally validated RFAN-ML, a ML model to predict renal function after nephrectomy, and have deployed our model online. RFAN-ML has the potential to improve the care and outcomes in patients with kidney tumors by informing personalized patient counseling and guiding surgical planning.
Ähnliche Arbeiten
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
2017 · 15.274 Zit.
Increased Survival in Pancreatic Cancer with nab-Paclitaxel plus Gemcitabine
2013 · 6.560 Zit.
Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma
2015 · 5.839 Zit.
Sunitinib versus Interferon Alfa in Metastatic Renal-Cell Carcinoma
2007 · 5.731 Zit.
Sorafenib in Advanced Clear-Cell Renal-Cell Carcinoma
2007 · 4.772 Zit.