An Interpretable Temporal Convolutional Network Model for Acute Kidney Injury Prediction in the Intensive Care Unit
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)（2021）
Key words
acute kidney injury prediction,critical diseases,patients,AKI,traditional machine learning methods,logistic regression,laboratory data,statistical features,predictive performance,statistical values,TCN-based model,patient,laboratory examination data,Hilbert-Schmidt independence criterion,temporal features,complete vital signs data,interpretable temporal convolutional network model,support vector machine,long-short term memory network,XGBoost,HSIC
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