Early Detection of Lung Cancer Risk Using Data Mining

Ahmed, Kawsar; Abdullah-Al-Emran, Abdullah-Al-Emran; Jesmin, Tasnuba; Mukti, Roushney Fatima; Rahman, Md. Zamilur; Ahmed, Farzana

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저자정보: Ahmed, Kawsar (Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University) Abdullah-Al-Emran, Abdullah-Al-Emran (Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University) Jesmin, Tasnuba (Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University) Mukti, Roushney Fatima (Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University) Rahman, Md. Zamilur (Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University) Ahmed, Farzana (Department of Mathematics and Natural Science, BRAC University)

저널정보: 아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제14권 제1호

발행연도: 2013.1

수록면: 595 - 598 (4page)

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Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed which is easy, cost effective and time saving. Materials and Methods: Initially 400 cancer and non-cancer patients' data were collected from different diagnostic centres, pre-processed and clustered using a K-means clustering algorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered using AprioriTid and a decision tree algorithm. Results: Finally using the significant pattern prediction tools for a lung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful in detection of a person's predisposition for lung cancer. Conclusions: Most of people of Bangladesh do not even know they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible. Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effective preventive strategy.

#Data mining #pre-processing #disease diagnosis #aprioriTid algorithm #DT algorithm #Bangladesh

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Ahmed, Kawsar

소속기관 Department of Information and Communication Technology, Mawlana Bhashani Science and Technology Univ