Naslov (eng)

OPPORTUNITIES FOR HEALTHCARE COST PREDICTION USING MACHINE LEARNING ALGORITHMS

Autor

Rakonjac-Antić, Tatjana
Koprivica, Marija
Kočović De Santo, Milica
Bradić, Kristina

Opis (eng)

Abstract: The growing trend of healthcare costs, increased life expectancy, and the increasing availability of data on policyholders indicate the importance of the application of machine learning in health insurance. Using historical data of policyholders, machine learning enables the prediction of healthcare costs, identification of high-risk individuals for hospitalisation, assessment of the likelihood of chronic diseases, and more. The subject of research in this paper are the opportunities for healthcare cost prediction by implementing different machine learning algorithms. Based on the public database from the Kaggle website, the created model incorporates various machine learning algorithms such as Random Forest, Gradient Boosting and Linear Regression. The aim of the paper is to point out that selecting a predictive machine learning model with the best performance can significantly improve the prediction of individual healthcare costs. This, in turn, contributes to determining appropriate premiums for voluntary health insurance.

Jezik

engleski

Datum

2024

Licenca

Ovo delo je licencirano pod uslovima licence
Creative Commons CC BY-NC-ND 4.0 - Creative Commons Autorstvo - Nekomercijalno - Bez prerada 4.0 International License.

http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

Predmet

Keywords: healthcare costs, health insurance, insurance premium, machine learning, database, Random Forest, Gradient Boosting, Linear Regression.

Deo kolekcije (1)

o:28218

Ekonomski fakultet