Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis. Issue 1 (30th July 2016)

• Record Type: Journal Article
• Authors: Dubey, Ashutosh Kumar; Gupta, Umesh; Jain, Sonal
• Is Part Of: Cancer communications. Volume 35:Issue 1(2016)
• Page Start: 1
• Page End: 13
• Publication Date: 2016-07-30
• Subjects: Lung cancer -- Incidence and mortality rates -- Data mining -- Evolutionary algorithms; Cancer -- Periodicals; Neoplasms; Electronic journals; Periodical; Fulltext; Internet Resources; Periodicals; Periodicals; 616.994005
• DOI: 10.1186/s40880-016-0135-x
• Languages: English
• ISSNs: 2523-3548

Abstract

Abstract: 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.