  Heart failure occurs when the heart is not able to pump blood and oxygen to
support other organs in the body as it should. Treatments include medications
and sometimes hospitalization. Patients with heart failure can have both
cardiovascular as well as non-cardiovascular comorbidities. Clinical notes of
patients with heart failure can be analyzed to gain insight into the topics
discussed in these notes and the major comorbidities in these patients. In this
regard, we apply machine learning techniques, such as topic modeling, to
identify the major themes found in the clinical notes specific to the
procedures performed on 1,200 patients admitted for heart failure at the
University of Illinois Hospital and Health Sciences System (UI Health). Topic
modeling revealed five hidden themes in these clinical notes, including one
related to heart disease comorbidities.
