Our Mul-arXiv:1912.00862v1 [cs.CL] 25 Nov 2019 tiResCNN model is composed of five layers: the input layer leverages word embeddings pre-trained by word2vec (Mikolov et al. 2013) ; the multi-filter convolutional layer consists of multiple convolutional filters (Kim 2014); the residual convolutional layer contains multiple residual blocks (He et al. 2016) ; the attention layer keeps the interpretability for the model following<cite> (Mullenbach et al. 2018)</cite> ; the output layer utilizes the sigmoid function to predict the probability of each ICD code.