Risk analysis of lung cancer and effects of stress level on cancer risk through neuro-fuzzy model

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dc.contributor.authorYilmaz, Atinc
dc.contributor.authorAri, Seckin
dc.contributor.authorKocabicak, Umit
dc.date.accessioned2024-03-13T10:30:58Z
dc.date.available2024-03-13T10:30:58Z
dc.date.issued2016
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractA significant number of people pass away due to limited medical resources for the battle with cancer. Fatal cases can be reduced by using the computational techniques in the medical and health system. If the cancer is diagnosed early, the chance of successful treatment increases. In this study, the risk of getting lung cancer will be obtained and patients will be provided with directions to exterminate the risk. After calculating the risk value for lung cancer, status of the patient's susceptibility and resistance to stress is used in determining the effects of stress to disease. In order to resolve the problem, the neuro-fuzzy logic model has been presented. When encouraging results are obtained from the study; the system will form a pre-diagnosis for the people who possibly can have risk of getting cancer due to working conditions or living standards. Therefore, this study will enable these people to take precautions to prevent the risk of cancer. In this study a new t-norm operator has been utilized in the problem. Finally, the performance of the proposed method has been compared to other methods. Beside this, the contribution of neuro-fuzzy logic model in the field of health and topics of artificial intelligence will also be examined in this study. (C) 2016 Elsevier Ireland Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.cmpb.2016.09.002
dc.identifier.endpage46en_US
dc.identifier.issn0169-2607
dc.identifier.issn1872-7565
dc.identifier.pmid28110738en_US
dc.identifier.scopus2-s2.0-84988632760en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage35en_US
dc.identifier.urihttps://doi.org/10.1016/j.cmpb.2016.09.002
dc.identifier.urihttps://hdl.handle.net/20.500.12662/3634
dc.identifier.volume137en_US
dc.identifier.wosWOS:000386750300005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherElsevier Ireland Ltden_US
dc.relation.ispartofComputer Methods And Programs In Biomedicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNeuro-fuzzy logicen_US
dc.subjectCanceren_US
dc.subjectRisken_US
dc.subjectLung canceren_US
dc.subjectStressen_US
dc.subjectEarly diagnosisen_US
dc.titleRisk analysis of lung cancer and effects of stress level on cancer risk through neuro-fuzzy modelen_US
dc.typeArticleen_US

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