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Advancing Cardiovascular Mortality Trend Analysis: A Machine Learning Approach to Predict Future Health Policy Needs.
- Source :
- Studies in Health Technology & Informatics; 2024, Vol. 316, p868-872, 5p
- Publication Year :
- 2024
-
Abstract
- This study investigates the forecasting of cardiovascular mortality trends in Greeceās elderly population. Utilizing mortality data from 2001 to 2020, we employ two forecasting models: the Autoregressive Integrated Moving Average (ARIMA) and Facebook's Prophet model. Our study evaluates the efficacy of these models in predicting cardiovascular mortality trends over 2020-2030. The ARIMA model showcased predictive accuracy for the general and male population within the 65-79 age group, whereas the Prophet model provided better forecasts for females in the same age bracket. Our findings emphasize the need for adaptive forecasting tools that accommodate demographic-specific characteristics and highlight the role of advanced statistical methods in health policy planning. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09269630
- Volume :
- 316
- Database :
- Complementary Index
- Journal :
- Studies in Health Technology & Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 179286380
- Full Text :
- https://doi.org/10.3233/SHTI240549