A multimodal survival model using attention-based histology features, RNA-seq encoders, and low-rank bilinear fusion shows improved performance over concatenation baselines on the CHIMERA dataset for HR-NMIBC.
Journal of the American Statistical Association53(282), 457–481 (1958)
2 Pith papers cite this work. Polarity classification is still indexing.
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SurvBench supplies a configurable, open-source preprocessing pipeline that standardizes multi-modal EHR data from four critical-care databases for single-risk and competing-risk survival analysis.
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Attention-Based Multimodal Survival Prediction with Cross-Modal Bilinear Fusion
A multimodal survival model using attention-based histology features, RNA-seq encoders, and low-rank bilinear fusion shows improved performance over concatenation baselines on the CHIMERA dataset for HR-NMIBC.
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SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysis
SurvBench supplies a configurable, open-source preprocessing pipeline that standardizes multi-modal EHR data from four critical-care databases for single-risk and competing-risk survival analysis.