AI RESEARCH
Causal-Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury
arXiv CS.LG
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ArXi:2604.20259v1 Announce Type: new Accurate early prediction of Acute Kidney Injury (AKI) is critical for timely clinical intervention. However, existing deep learning models struggle with irregularly sampled data and suffer from the opaque "black-box" nature of sequential architectures, strictly limiting clinical trust. To address these challenges, we propose CT-Former, integrating continuous-time modeling with a Causal-Transformer.