ArXiv Preprint
Understanding deep learning model behavior is critical to accepting machine
learning-based decision support systems in the medical community. Previous
research has shown that jointly using clinical notes with electronic health
record (EHR) data improved predictive performance for patient monitoring in the
intensive care unit (ICU). In this work, we explore the underlying reasons for
these improvements. While relying on a basic attention-based model to allow for
interpretability, we first confirm that performance significantly improves over
state-of-the-art EHR data models when combining EHR data and clinical notes. We
then provide an analysis showing improvements arise almost exclusively from a
subset of notes containing broader context on patient state rather than
clinician notes. We believe such findings highlight deep learning models for
EHR data to be more limited by partially-descriptive data than by modeling
choice, motivating a more data-centric approach in the field.
Severin Husmann, Hugo Yèche, Gunnar Rätsch, Rita Kuznetsova
2022-12-06
