Predictive Disease Data Analysis of Air Pollution Using Supervised Learning

Autor: null Manikanta Sirigineedi, null Padma Bellapukonda, null R N V Jagan Mohan
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Scientific Research in Computer Science, Engineering and Information Technology. :105-110
ISSN: 2456-3307
DOI: 10.32628/cseit2283118
Popis: Air pollution is a combination of natural and manmade substances in the air we breathe. It is classified into two major categories, i.e. outdoor air pollution and indoor air pollution. Outdoor air pollution involves exposures that take place outside the built environment where as, indoor air pollution involves exposure to particulates, carbon oxides, and other pollutants carried by indoor air or dust. In this paper, we would like to propose that air pollution relates to increased cardiovascular and breathing related problems data rate, prediction with supervised machine learning. The study is largest of its benevolent to investigate the short-term impacts of air pollution is conducted completed a 30-years epoch. This study analyzes the experiments data on air pollution and humanity in India and other regions. The experimental result is on Risk of Cardiovascular Illness in several patients data classification is used.
Databáze: OpenAIRE