Earticle

초록

영어

The best marker combination for differentiating the ovarian cancer from benign is explored with the logistic regression. The serum samples from 81 patients with ovarian cancer and 216 patients with benign pelvic masses provided by 2 institutes were analyzed using Luminex assay test. The selection performance of the logistic regression was compared with three other methods such as t-test, genetic algorithm, and random forest. The evaluation of the four methods were performed also with three classification methods including logistic regression, linear discriminant analysis, and k-nearest neighbor method. The 4 marker combination from the logistic regression showed the best performance against the other selection methods in terms of the average accuracy.

목차

Abstract
 1. Introduction
 2. Method
 3. Results
 5. Conclusion
 Acknowledgments
 References

키워드

저자

• Yu-Seop Kim [ Dept. of Ubiquitous Computing, Hallym University, Bio-IT Research Center, Hallym University ]
• Min-Ki Jang [ Dept of Computer Engineering, Hallym University, Bio-IT Research Center, Hallym University ]
• Chan-Young Park [ Dept. of Ubiquitous Computing, Hallym University, Bio-IT Research Center, Hallym University ]
• Hye-Jeong Song [ Dept. of Ubiquitous Computing, Hallym University, Bio-IT Research Center, Hallym University ]
• Jong-Dae Kim [ Dept. of Ubiquitous Computing, Hallym University, Bio-IT Research Center, Hallym University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605