SAMVAE integrates clinical, multi-omics, and pathology image data in a variational autoencoder for continuous-time survival analysis with competing risks, with experiments on two TCGA cancer cohorts.
Nonparametric estimation from incomplete observations
3 Pith papers cite this work. Polarity classification is still indexing.
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LLM judges for human-AI coding co-creation show moderate performance (ROC-AUC 0.59) and low agreement, with co-creation success concentrating early in interactions.
A framework integrating explainable AI for feature attribution, survival analysis for time-to-churn modeling, and RFM profiling for behavioral segmentation to support interpretable retention strategies in online retail.
citing papers explorer
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Deep Survival Analysis in Multimodal Medical Data: A Parametric and Probabilistic Approach with Competing Risks
SAMVAE integrates clinical, multi-omics, and pathology image data in a variational autoencoder for continuous-time survival analysis with competing risks, with experiments on two TCGA cancer cohorts.
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LLM-as-a-Judge for Human-AI Co-Creation: A Reliability-Aware Evaluation Framework for Coding
LLM judges for human-AI coding co-creation show moderate performance (ROC-AUC 0.59) and low agreement, with co-creation success concentrating early in interactions.
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Explainability, risk modeling, and segmentation based customer churn analytics for personalized retention in e-commerce
A framework integrating explainable AI for feature attribution, survival analysis for time-to-churn modeling, and RFM profiling for behavioral segmentation to support interpretable retention strategies in online retail.