This document presents research on using deep learning models to predict mortality for patients in the intensive care unit (ICU). The study uses the MIMIC-II dataset to evaluate models. It first discusses related work on ICU mortality prediction using machine learning. It then describes preprocessing the MIMIC-II data, which includes clustering repeated variables within each hour. Two models are evaluated: a recurrent neural network-long short term memory (RNN-LSTM) model and a convolution neural network (CNN) model. Evaluation metrics show the CNN model achieves higher precision, F1, and AUC scores compared to the RNN-LSTM model. Therefore, the CNN model may be better suited at mortality prediction tasks.