How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries
Improving life expectancy, which is falling and declining globally, is getting harder, especially given the limited economic resources in most parts of the world. This study seeks to identify the most significant factors that positively and negatively affect life expectancy, separating them from les...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | International Journal of Information Management Data Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096823000150 |
| _version_ | 1797847673044205568 |
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| author | Akanmode Eyitayo Ronmi Rajesh Prasad Baku Agyo Raphael |
| author_facet | Akanmode Eyitayo Ronmi Rajesh Prasad Baku Agyo Raphael |
| author_sort | Akanmode Eyitayo Ronmi |
| collection | DOAJ |
| description | Improving life expectancy, which is falling and declining globally, is getting harder, especially given the limited economic resources in most parts of the world. This study seeks to identify the most significant factors that positively and negatively affect life expectancy, separating them from less significant factors. This way, specific areas can be identified to channel scarce economic resources towards increasing life expectancy. Using data science techniques on a dataset comprising economic, immunological, health, personal, and social attributes, we have been able to achieve this. Furthermore, four machine learning tree regression algorithms were employed using the identified attributes to develop and evaluate life expectancy prediction models. The extremely randomized tree model performed best using evaluation matrices: MAE, RMSE, R2, and CV score. This research can help governments, especially in low-income, developing countries, make better decisions and investments, as well as help digital health experts develop technologies that could improve life expectancy. |
| first_indexed | 2024-04-09T18:15:13Z |
| format | Article |
| id | doaj.art-07cf5a7c3a954167b881a41a085149a4 |
| institution | Directory Open Access Journal |
| issn | 2667-0968 |
| language | English |
| last_indexed | 2024-04-09T18:15:13Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Information Management Data Insights |
| spelling | doaj.art-07cf5a7c3a954167b881a41a085149a42023-04-13T04:27:26ZengElsevierInternational Journal of Information Management Data Insights2667-09682023-04-0131100168How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countriesAkanmode Eyitayo Ronmi0Rajesh Prasad1Baku Agyo Raphael2Department of Computer Science, Federal University, Wukari, NigeriaDepartment of Computer Science and Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, India; Corresponding author.Department of Computer Science, Federal University, Wukari, NigeriaImproving life expectancy, which is falling and declining globally, is getting harder, especially given the limited economic resources in most parts of the world. This study seeks to identify the most significant factors that positively and negatively affect life expectancy, separating them from less significant factors. This way, specific areas can be identified to channel scarce economic resources towards increasing life expectancy. Using data science techniques on a dataset comprising economic, immunological, health, personal, and social attributes, we have been able to achieve this. Furthermore, four machine learning tree regression algorithms were employed using the identified attributes to develop and evaluate life expectancy prediction models. The extremely randomized tree model performed best using evaluation matrices: MAE, RMSE, R2, and CV score. This research can help governments, especially in low-income, developing countries, make better decisions and investments, as well as help digital health experts develop technologies that could improve life expectancy.http://www.sciencedirect.com/science/article/pii/S2667096823000150Data analysisLife expectancy factorsData scienceMachine learningAnd python programming |
| spellingShingle | Akanmode Eyitayo Ronmi Rajesh Prasad Baku Agyo Raphael How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries International Journal of Information Management Data Insights Data analysis Life expectancy factors Data science Machine learning And python programming |
| title | How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries |
| title_full | How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries |
| title_fullStr | How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries |
| title_full_unstemmed | How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries |
| title_short | How can artificial intelligence and data science algorithms predict life expectancy - An empirical investigation spanning 193 countries |
| title_sort | how can artificial intelligence and data science algorithms predict life expectancy an empirical investigation spanning 193 countries |
| topic | Data analysis Life expectancy factors Data science Machine learning And python programming |
| url | http://www.sciencedirect.com/science/article/pii/S2667096823000150 |
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