Topics: eHealth, Health monitoring, e-Health applications

SOURCE: MDPI Open Access Journals, 2021, Feb. ;  BOOK DOI Link, Chapter DOI Link

Risk Assessment for Personalized Health Insurance Based on Real-World Data

Aristodemos Pnevmatikakis 1* ; Efstathios Kanavos 1; George Matikas1 ; Konstantina Kostopoulou1 ; Alfredo Cesario1,2 ; Sofoklis Kyriazakos 1,3

1   Innovation Sprint Sprl, Clos Chapelle-aux-Champs 30, 1200 Brussels, Belgium
2   Scientific Directorate, Fondazione Policlinico A. Gemelli IRCCS, 00168 Rome, Italy
3   Business Development and Technology Department, School of Business and Social Sciences, Aarhus University, Birk Centerpark 15, 7400 Herning, Denmark
*   Author to whom correspondence should be addressed

Abstract

The way one leads their life is considered an important factor in health. In this paper we propose a system to provide risk assessment based on behavior for the health insurance sector. To do so we built a platform to collect real-world data that enumerate different aspects of behavior, and a simulator to augment actual data with synthetic. Using the data, we built classifiers to predict variations in important quantities for the lifestyle of a person. We offer a risk assessment service to the health insurance professionals by manipulating the classifier predictions in the long-term. We also address virtual coaching by using explainable Artificial Intelligence (AI) techniques on the classifier itself to gain insights on the advice to be offered to insurance customers.

Keywords: machine learning; classification; explainable AI; risk assessment

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