The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models

The Concordance Index (C-index) is a commonly used metric in Survival Analysis for evaluating the performance of a prediction model. In this paper, we propose a decomposition of the C-index into a weighted harmonic mean of two quantities: one for ranking observed events versus other observed events,...

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Veröffentlicht in:	Artificial intelligence in medicine Jg. 148; S. 102781
Hauptverfasser:	Alabdallah, Abdallah, Ohlsson, Mattias, Pashami, Sepideh, Rögnvaldsson, Thorsteinn
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.02.2024
Schlagworte:	artificial neural network Bioinformatics Computer Concordance Index Deep learning Encoder-decoder Evaluation Metric Evaluation metrics Fine-grained analysis Forecasting Learning systems Machine Learning Matematik Mathematical Sciences Natural Sciences Naturvetenskap Neural Networks Prediction modelling Probability Theory and Statistics Sannolikhetsteori och statistik Signal encoding Survival Analysis Survival prediction Variational Encoder-Decoder Weighted harmonic means Survival analysis Variational encoder–decoder Evaluation metric Concordance Index
ISSN:	0933-3657, 1873-2860, 1873-2860
Online-Zugang:	Volltext
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