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Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis
BACKGROUND: Owing to the use of tobacco and the consumption of alcohol and adulterated food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since the last decade of the twentieth century, lung cancer has been the most common cancer type. This study aimed to determine t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967338/ https://www.ncbi.nlm.nih.gov/pubmed/27473753 http://dx.doi.org/10.1186/s40880-016-0135-x |
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author | Dubey, Ashutosh Kumar Gupta, Umesh Jain, Sonal |
author_facet | Dubey, Ashutosh Kumar Gupta, Umesh Jain, Sonal |
author_sort | Dubey, Ashutosh Kumar |
collection | PubMed |
description | BACKGROUND: Owing to the use of tobacco and the consumption of alcohol and adulterated food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since the last decade of the twentieth century, lung cancer has been the most common cancer type. This study aimed to determine the global status of lung cancer and to evaluate the use of computational methods in the early detection of lung cancer. METHODS: We used lung cancer data from the United Kingdom (UK), the United States (US), India, and Egypt. For statistical analysis, we used incidence and mortality as well as survival rates to better understand the critical state of lung cancer. RESULTS: In the UK and the US, we found a significant decrease in lung cancer mortalities in the period of 1990–2014, whereas, in India and Egypt, such a decrease was not much promising. Additionally, we observed that, in the UK and the US, the survival rates of women with lung cancer were higher than those of men. We observed that the data mining and evolutionary algorithms were efficient in lung cancer detection. CONCLUSIONS: Our findings provide an inclusive understanding of the incidences, mortalities, and survival rates of lung cancer in the UK, the US, India, and Egypt. The combined use of data mining and evolutionary algorithm can be efficient in lung cancer detection. |
format | Online Article Text |
id | pubmed-4967338 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49673382016-08-02 Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis Dubey, Ashutosh Kumar Gupta, Umesh Jain, Sonal Chin J Cancer Original Article BACKGROUND: Owing to the use of tobacco and the consumption of alcohol and adulterated food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since the last decade of the twentieth century, lung cancer has been the most common cancer type. This study aimed to determine the global status of lung cancer and to evaluate the use of computational methods in the early detection of lung cancer. METHODS: We used lung cancer data from the United Kingdom (UK), the United States (US), India, and Egypt. For statistical analysis, we used incidence and mortality as well as survival rates to better understand the critical state of lung cancer. RESULTS: In the UK and the US, we found a significant decrease in lung cancer mortalities in the period of 1990–2014, whereas, in India and Egypt, such a decrease was not much promising. Additionally, we observed that, in the UK and the US, the survival rates of women with lung cancer were higher than those of men. We observed that the data mining and evolutionary algorithms were efficient in lung cancer detection. CONCLUSIONS: Our findings provide an inclusive understanding of the incidences, mortalities, and survival rates of lung cancer in the UK, the US, India, and Egypt. The combined use of data mining and evolutionary algorithm can be efficient in lung cancer detection. BioMed Central 2016-07-30 /pmc/articles/PMC4967338/ /pubmed/27473753 http://dx.doi.org/10.1186/s40880-016-0135-x Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Original Article Dubey, Ashutosh Kumar Gupta, Umesh Jain, Sonal Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
title | Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
title_full | Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
title_fullStr | Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
title_full_unstemmed | Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
title_short | Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
title_sort | epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967338/ https://www.ncbi.nlm.nih.gov/pubmed/27473753 http://dx.doi.org/10.1186/s40880-016-0135-x |
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