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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Bibliographic Details
Published in:	Artificial intelligence in medicine Vol. 148; p. 102781
Main Authors:	Alabdallah, Abdallah, Ohlsson, Mattias, Pashami, Sepideh, Rögnvaldsson, Thorsteinn
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.02.2024
Subjects:	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 Access:	Get full text
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