gp-1108/air_pollution_ai

Correlation between air quality and respiratory diseases

Summary

The prediction of mortality rates for respiratory diseases based on air pollutant levels is a critical task in understanding and mitigating the impacts of environmental factors on public health. In this paper, we describe a machine learning model that uses data on air pollutants to predict respiratory disease mortality rates. A dataset containing historical records of pollutant concentrations and mortality rates associated with respiratory diseases was used to create and evaluate the model. We used a multi-step method that included data preparation, implementation of machine learning algorithms and experimental analysis. The performance of the final model are pretty got and they highlight the correlation between the data. This study presents an in-depth analysis of our approach, experimental design, results and analysis, highlighting the advantages and disadvantages of our model. In order to improve the accuracy and usefulness of mortality rate prediction models for respiratory disorders, we explore the consequences of our results and provide suggestions for future research areas.

Team

• Pietro Girotto (https://github.com/gp-1108)
• Enrico D'Alberton (https://github.com/enricopro)
• Arjun Jassal (https://github.com/Faldrus)