Analyzing key health factors influencing life expectancy using machine learning

Abstract

With the rapid development of global medical technology and the steady improvement of social living standards, life expectancy per capita has become one of the most important indicators of a country or region's level of development. It not only reflects the quality of life and health of the local people, but also profoundly affects the economic growth and social stability of the country. In underdeveloped countries, life expectancy at birth is generally lower than in more developed countries due to resource constraints and poor medical facilities. This phenomenon has triggered extensive research interest in whether there is some correlation between life expectancy per capita and economic growth, and how improving life expectancy can contribute to a country's economic transformation and development. The purpose of this paper is to explore the impact of life expectancy per capita on economic growth and how to promote the economic transformation and development of countries by increasing life expectancy. Through a comparative study of Asian countries such as China, Singapore and Japan, this paper analyzes the impact of different factors on life expectancy through technical methods such as visual analysis, hypothesis testing, regression modeling, and decision tree modeling, and explores how these factors play a role in economic growth. The results of this study may have some guiding significance for improving life expectancy.