Deep Kernel Aalen-Johansen Estimator: An Interpretable and Flexible Neural Net Framework for Competing Risks Article Swipe
Shen, Xiaobin
,
Chen, George H.
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2512.08063
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2512.08063
We propose an interpretable deep competing risks model called the Deep Kernel Aalen-Johansen (DKAJ) estimator, which generalizes the classical Aalen-Johansen nonparametric estimate of cumulative incidence functions (CIFs). Each data point (e.g., patient) is represented as a weighted combination of clusters. If a data point has nonzero weight only for one cluster, then its predicted CIFs correspond to those of the classical Aalen-Johansen estimator restricted to data points from that cluster. These weights come from an automatically learned kernel function that measures how similar any two data points are. On four standard competing risks datasets, we show that DKAJ is competitive with state-of-the-art baselines while being able to provide visualizations to assist model interpretation.
Related Topics
Concepts
Nonparametric statistics
Kernel (algebra)
Estimator
Computer science
Artificial intelligence
Function (biology)
Artificial neural network
Kernel method
Deep neural networks
Data point
Point (geometry)
Mathematics
Kernel density estimation
Data mining
Machine learning
Point process
Variable kernel density estimation
Algorithm
Score
Net (polyhedron)
Kernel smoother
Point estimation
Real world data
Data modeling
Pattern recognition (psychology)
Weight function
Interpretability
Support vector machine
Metadata
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- preprint
- Landing Page
- https://doi.org/10.48550/arxiv.2512.08063
- OA Status
- green
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https://doi.org/10.48550/arxiv.2512.08063Digital Object Identifier
- Title
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Deep Kernel Aalen-Johansen Estimator: An Interpretable and Flexible Neural Net Framework for Competing RisksWork title
- Type
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preprintOpenAlex work type
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2025Year of publication
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2025-12-08Full publication date if available
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Shen, Xiaobin, Chen, George H.List of authors in order
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https://doi.org/10.48550/arxiv.2512.08063Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://doi.org/10.48550/arxiv.2512.08063Direct OA link when available
- Concepts
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Nonparametric statistics, Kernel (algebra), Estimator, Computer science, Artificial intelligence, Function (biology), Artificial neural network, Kernel method, Deep neural networks, Data point, Point (geometry), Mathematics, Kernel density estimation, Data mining, Machine learning, Point process, Variable kernel density estimation, Algorithm, Score, Net (polyhedron), Kernel smoother, Point estimation, Real world data, Data modeling, Pattern recognition (psychology), Weight function, Interpretability, Support vector machineTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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