Enhance the after-discharge mortality rate prediction via learning from the medical notes

ArXi:2605.03560v1 Announce Type: new With the increase of the Electronic Health Records (EHR) data, and researchers are developing machine learning models to learn from the medical notes. These unstructured text data pose significant challenges on the learning process as the quality of data is low. These data are often messy, repetitive and redundant. We have shown these notes data to be informative by conducting the after-discharge mortality rate prediction task. The AUC-ROC for models using the medical note information is generally 0.1 higher than those without the medical notes.