Earticle

초록

영어

In this study, a new diagnosis model based on multiple serum biomarkers and meno-pausal information was developed for the early detection of ovarian cancer. A total of 254 serum samples from 202 patients with benign tumors and 52 patients with ovarian cancer were used. The concentrations of 22 ovarian-cancer-specific serum biomarkers were de-termined using Luminex, and premenopausal and postmenopausal status was binary mapped as 0 and 1. To identify the best biomarker combinations effectively differentiating ovarian cancer from benign tumors, all combinations with 2 and 3 biomarkers were eval-uated according to the area under the receiver operating characteristic curve (AUC). Menopausal information was included in the combinations of 2 and 3 biomarkers that showed the best classification performance, with AUC values of 84.53 and 87.01, respec-tively. The diagnosis model for ovarian cancer developed in this study based on the best biomarker combinations proved that combinations of biomarkers together with menopau-sal information show more accurate performance than mere combinations of biomarkers alone.

목차

Abstract
 1. Introduction
 2. Data Collection
 3. Methods
 4. Results
 5. Conclusion
 Acknowledgments
 References

키워드

저자

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