We present a deep learning system that advances the state of the art for the MIMIC-III dataset, achieving a new best micro F1-measure of 55.85%, significantly outperforming the previous best result<cite> (Mullenbach et al., 2018)</cite> . We achieve this through a number of enhancements, including two major novel contributions: multiview convolutional channels, which effectively learn to adjust kernel sizes throughout the input; and attention regularization, mediated by natural-language code descriptions, which helps overcome sparsity for thousands of uncommon codes.