会议论文详细信息
9th Annual Basic Science International Conference 2019
Possibilistics C-Means (PCM) Algorithm for the Hepatocellular Carcinoma (HCC) Classification
自然科学(总论)
Khairi, Rafiqatul^1 ; Rustam, Zuherman^1 ; Utama, Suarsih^1
Department of Mathematics, University of Indonesia, Depok
16424, Indonesia^1
关键词: Alphafetoprotein (AFP);    Blood test;    Early diagnosis;    Hepatocellular carcinoma;    Liver cancer cells;    Liver cancers;    Malignant tumors;    Possibilistic C-means;   
Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/546/5/052038/pdf
DOI  :  10.1088/1757-899X/546/5/052038
学科分类:自然科学(综合)
来源: IOP
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【 摘 要 】

Hepatocellular Carcinoma (HCC) is a malignant tumor that attacks the liver and can cause death. Although there have been advances in technology for the prevention, diagnosis, and treatment, the number of liver cancer patients is still increasing. The liver can still function normally even if some of its parts are not in good condition. Therefore, the symptoms of liver cancer at an early stage are difficult to detect. Early diagnosis of this disease will increase the chances of recovery. One method to diagnose Hepatocellular Carcinoma (HCC) is to check the level of alpha-fetoprotein (AFP) in the blood which is alpha-fetoprotein (AFP) is a cancer index. If the liver cancer cells continue to grow, the level of alpha-fetoprotein (AFP) will be very high. This paper presents a Possibilistic C-Means (PCM) algorithm, which used to classify the results of alpha-fetoprotein (AFP) blood tests to determine whether patients diagnosed with Hepatocellular Carcinoma (HCC) or normal patients. This method will help to get an accuracy of about 92%.

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