A Cancer Prediction Method Based on Principal Component Analysis and Support Vector Machine
Ovarian cancer is one of the most common cancers contracted by women in China，and it has a tendency to increase year by year. The gene chip is widely applied to the early detection of cancer，which ensures an increase in survival rate over 97%. In this paper，by virtue of a mass spectrometry data of...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2021-06-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1977 |
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| Summary: | Ovarian cancer is one of the most common cancers contracted by women in China，and it has a
tendency to increase year by year. The gene chip is widely applied to the early detection of cancer，which ensures
an increase in survival rate over 97%. In this paper，by virtue of a mass spectrometry data of gene chip，an ovarian
cancer prediction method based on principal component analysis ( PCA) and support vector machine ( SVM) is
proposed. The model is designed and the simulation comparison experiments are carried out，which are at the core
of the research. The experimental results verify that the proposed method has presented the superior performance
with prediction accuracy of 89. 1%and CPU time of 4. 791 s. |
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| ISSN: | 1007-2683 |