$\textbf{Materials and Methods}$ We use the real-world clinical notes from MIMIC-III, a freely available dataset consisting of clinical data of more than forty thousand patients who stayed in intensive care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. We proposed a Convolutional Neural Network model to learn semantic features from unstructured textual input and automatically predict primary discharge diagnosis. 
