Robust pattern matching algorithm for cervical cancer detection using protein sequence

Abstract

Cancer has been characterized as a heterogeneous disease consisting of many newlinedifferent subtypes. The early diagnosis and prognosis of a cancer type have more newlineattention in cancer research and this will provide a great facilitate the subsequent newlineclinical management of patients. Cervical Cancer is one of the most commonly newlineaffected cancers for most of the Women between age group of 31 to 45. Cervical newlinecancer is a cancer arising from the cervix. It is due to the abnormal growth of cells newlinethat have the ability to invade or spread to other parts of the body. The cervical cancer newlineaffected patients are classified into high or low risk groups have led many research newlineteams, from the biomedical and the bioinformatics field. Most of the research peoples newlineare working towards the cancer classification fields in the computational biology. In newlinethis paper, we develop a model for Cervical Cancer detection using Probabilistic newlineApproach. In the proposed method, we have taken simple population based newlineprobabilistic approach for effective detection of Cervical Cancer by using protein newlinesequence. The proposed scheme is implemented with the created dataset from newlineavailable information in CCDB and this dataset is used for training the system. We newlinehave presented the result and detection accuracy of the proposed scheme. The initial newlinestage of evaluation provides good result for the early detection of cervical cancer newlineusing protein sequence. newline newline newline