Prior Detection of a Person’s Risk Level of Getting Suffered from Liver Cancer
Meenu Sharma1, Rafat Parveen2
1Meenu Sharma*, Department of Computer Science, Jamia Millia Islamia, Jamia Nagar New Delhi, India.
2Dr. Rafat Parveen Department of Computer Science, Jamia Millia Islamia, Jamia Nagar New Delhi, India.
Manuscript received on October 17, 2019. | Revised Manuscript received on 24 October, 2019. | Manuscript published on November 10, 2019. | PP: 629-637 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4505119119/2019©BEIESP | DOI: 10.35940/ijitee.A4505.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Liver Cancer becomes a major problem globally because it is responsible for the majority of death. Identification of various Risk factors which can be either genetic or environmental becomes necessary for early detection of Liver Cancer. To solve this problem, the data has been collected from various diagnostic centres, the data consists of 100 cancerous and 100 non-cancerous/healthy persons, then significant frequent patterns are identified by using the Apriori Algorithm. By employing significant frequent pattern, a prediction technique has been developed which identify the person susceptibility toward Liver Cancer by using the Risk Factors. Most peoples do not know that they are suffering from Liver Cancer at the early stage of cancer, and when they knew, that time it becomes impossible to cure. So, for proper cure Early detection of Liver Cancer acquires a necessary step in its diagnosis process, and for making a powerful preventive approach. This prediction system can effectively and successfully predict the Liver Cancer Risk, and it has been predicted in the form of three stages that is low Risk, medium Risk or high Risk. This approach can be used in hospitals for diagnosis of Liver Cancer patients.
Keywords: Apriori Algorithm, Data Mining, Liver, and Liver Cancer
Scope of the Article: Data Mining