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Combining Survival Analysis and Neural Networks to predict Life Expectancy

Lazaros Iliadis, Kyriaki Kitikidou, Kassiani Skoularik

Abstract


This paper aims to shed light in the contribution of determinants to the health status of the population and to provide evidence on whether or not these determinants are producing similar results, in the countries of the Organization for Economic Co-operation and Development (OECD). This is done by employing two different approaches, namely Cox regression and Artificial Neural Networks in. In this study, one output – Life Expectancy (LE) at birth of the total population – and seven inputs are included. The inputs represent the three main dimensions of health outcome production: health resources (measured by health spending or the number of health practitioners), socioeconomic environment (pollution, education and income) and lifestyle (tobacco, alcohol and diet). A variable expressing country specificities is also used. The two distinct approaches performed reached the same conclusion, that health resources and country specific effects are more closely related to LE

Keywords


Artificial Neural Networks, Cox regression, Health status, Survival analysis.

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