What's in a Note? Unpacking Predictive Value in Clinical Note Representations

Unlocking the full potential of clinical notes within electronic health records presents a challenge for large scale, computational analyses. Many studies that incorporate information from clinical notes do so with simple word-matching approaches and a focused goal of improving performance in a specific task such as mortality prediction. Our project explores representation strategies for clinical text and how to combine many words into larger document-level representations. The code and model shared here are supplements to the AMIA 2018 Informatics Summit paper of the same name.