Classification of Indicators based on Morbidity and Mortality

 

YEAR : 2023

 

Description

One of the primary goals of epidemiology is to quantify various aspects of a population’s health, illness, and death status and the determinants (or risk factors) thereof by calculating health indicators that measure the magnitudes of various conditions. There has been some confusion regarding health indicators, with discrepancies in usage among organizations such as the World Health Organization the, Centers for Disease Control and Prevention (CDC), and the CDC of other countries, and the usage of the relevant terminology may vary across papers. Therefore, in this review, we would like to propose appropriate terminological definitions for health indicators based on the most commonly used meanings and/or the terms used by official agencies, in order to bring clarity to this area of confusion. We have used appropriate examples to make each health indicator easy for the reader to understand. We have included practical exercises for some health indicators to help readers understand the underlying concepts. By using Machine learning algorithms we classify and analysis which indicator represents the mobidity and mortality rate. While compare to other algorithms bagging classifier give more accuracy.

 

ADDITIONAL INFORMATION

HARDWARE REQUIREMENTS:
•Operating System : Windows 7,8,10 (64 bit)
•Software : Python
•Tools : Anaconda (Jupyter notebook IDE)
SOFTWARE REQUIREMENTS:
•Hard Disk : 500GB and above
•RAM : 4GB and above
•Processor : I5 and above

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