Using the Random Forest Algorithm for Searching Behavior Patterns in Electronic Health Records
Date
2019-05-05Author
Fuente, C. de la
Urrutia, A.
Chávez, E.
Publisher
IEEE LATIN AMERICA TRANSACTIONSDescription
Metadata
Show full item recordAbstract
The search for information associated with
qualitative data is usually done using data mining algorithms, the
presented research analyzes data of patients with essential
hypertension (HTA), patients who have developed hypertension
but there is no clear reason why it has occurred. In this research,
a search of behavioral patterns was performed in the data
associated with the clinical records of 8470 patients using the
Random Forest algorithm. As a case study, the proposal focuses
on finding the relationship between the different pathologies or
factors associated to Hypertensive patients (other diseases for
example). The findings validate the right use of the algorithm due
to the results obtained agrees with the knowledge defined and
validated in the literature. Thus, trivial knowledge can be obtained
with the algorithm used. However, non-trivial knowledge was also
obtained given the analysis performed on a total of 4408 data of
female patients and 4062 of male patients showed a great
difference between the factors or pathologies that a patient
presents when classified according to their sex, thus another deep
study must be carried out closely with experts in the area of the
health as future research.