Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment.

Autor: Singh T; Guru Tegh Bahadur Institute of Technology, New Delhi, India., Kaur A; Guru Tegh Bahadur Institute of Technology, New Delhi, India., Katyal SK; Guru Tegh Bahadur Institute of Technology, New Delhi, India., Walia SK; Guru Tegh Bahadur Institute of Technology, New Delhi, India., Dhand G; Maharaja Surajmal Institute of Technology, New Delhi, India., Sheoran K; Maharaja Surajmal Institute of Technology, New Delhi, India., Mohanty SN; School of Computer Science and Engineering, VIT-AP University, Vijayawada, Andhra Pradesh, India., Khan MI; Department of Mechanical Engineering, Lebanese American University, Beirut, Lebanon. scientificresearchglobe@gmail.com.; Department of Mechanics and Engineering Science, Peking University, Beijing, 100871, China. scientificresearchglobe@gmail.com., Awwad FA; Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, 11587, Riyadh, Saudi Arabia., Ismail EAA; Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, 11587, Riyadh, Saudi Arabia.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Nov 20; Vol. 13 (1), pp. 20256. Date of Electronic Publication: 2023 Nov 20.
DOI: 10.1038/s41598-023-47705-5
Abstrakt: The Air Quality Index (AQI) in India is steadily deteriorating, leading to a rise in the mortality rate due to Lung Cancer. This decline in air quality can be attributed to various factors such as PM 2.5, PM 10, and Ozone (O3). To establish a relationship between AQI and Lung Cancer, several predictive models including Linear Regression, KNN, Decision Tree, ANN, Random Forest Regression, and XGBoost Regression were employed to estimate pollutant levels and Air Quality Index in India. The models relied on publicly available state-wise Air Pollution Dataset. Among all the models, the XGBoost Regression displayed the highest accuracy, with pollutant level estimations reaching an accuracy range of 81% to 98% during training and testing. The second-highest accuracy range was achieved by Random Forest. The paper also explores the impact of increasing pollution levels on the rising mortality rate among lung cancer patients in India.
(© 2023. The Author(s).)
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje