The authors have a dataset of 780 electronic health records and they use it to detect various medical events such as adverse drug events, drug dosage, etc. The task is done by assigning a label to each word in the document.
Annotation statistics for the corpus of health records.
They look at CRFs, LSTMs and GRUs. Both LSTMs and GRUs outperform the CRF, but the best performance is achieved by a GRU trained on whole documents.
The basic approach is an RNN applied to text to predict a medical event such as an ICD code. It is unclear if the complicated Bi-RNN model is required.
This has some useful applications such as
- Adapt old databases
- Correct errors
- Upgrade ICD versions
A simple diagram of an RNN applied to medical next is shown below: