Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment
Abstract 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, severa...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-47705-5 |
| _version_ | 1797453132393873408 |
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| author | Tamanpreet Singh Amandeep Kaur Sharon Kaur Katyal Simran Kaur Walia Geetika Dhand Kavita Sheoran Sachi Nandan Mohanty M. Ijaz Khan Fuad A. Awwad Emad A. A. Ismail |
| author_facet | Tamanpreet Singh Amandeep Kaur Sharon Kaur Katyal Simran Kaur Walia Geetika Dhand Kavita Sheoran Sachi Nandan Mohanty M. Ijaz Khan Fuad A. Awwad Emad A. A. Ismail |
| author_sort | Tamanpreet Singh |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-09T15:18:30Z |
| format | Article |
| id | doaj.art-67821265070a4ba1ac6ed374c00e65d3 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:18:30Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-67821265070a4ba1ac6ed374c00e65d32023-11-26T12:57:58ZengNature PortfolioScientific Reports2045-23222023-11-0113111210.1038/s41598-023-47705-5Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessmentTamanpreet Singh0Amandeep Kaur1Sharon Kaur Katyal2Simran Kaur Walia3Geetika Dhand4Kavita Sheoran5Sachi Nandan Mohanty6M. Ijaz Khan7Fuad A. Awwad8Emad A. A. Ismail9Guru Tegh Bahadur Institute of TechnologyGuru Tegh Bahadur Institute of TechnologyGuru Tegh Bahadur Institute of TechnologyGuru Tegh Bahadur Institute of TechnologyMaharaja Surajmal Institute of TechnologyMaharaja Surajmal Institute of TechnologySchool of Computer Science and Engineering, VIT-AP UniversityDepartment of Mechanical Engineering, Lebanese American UniversityDepartment of Quantitative Analysis, College of Business Administration, King Saud UniversityDepartment of Quantitative Analysis, College of Business Administration, King Saud UniversityAbstract 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.https://doi.org/10.1038/s41598-023-47705-5 |
| spellingShingle | Tamanpreet Singh Amandeep Kaur Sharon Kaur Katyal Simran Kaur Walia Geetika Dhand Kavita Sheoran Sachi Nandan Mohanty M. Ijaz Khan Fuad A. Awwad Emad A. A. Ismail Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment Scientific Reports |
| title | Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment |
| title_full | Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment |
| title_fullStr | Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment |
| title_full_unstemmed | Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment |
| title_short | Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment |
| title_sort | exploring the relationship between air quality index and lung cancer mortality in india predictive modeling and impact assessment |
| url | https://doi.org/10.1038/s41598-023-47705-5 |
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