Intraoperative Diagnosis Support Tool for Serous Ovarian Tumors Based on Microarray Data Using Multicategory Machine Learning.

Journal: International journal of gynecological cancer : official journal of the International Gynecological Cancer Society
PMID: 26512784

Abstract

OBJECTIVES: Serous borderline ovarian tumors (SBOTs) are a subtype of serous ovarian carcinoma with atypical proliferation. Frozen-section diagnosis has been used as an intraoperative diagnosis tool in supporting the fertility-sparing surgery by diagnosing SBOTs with accuracy of 48% to 79%. Using DNA microarray technology, we designed multicategory classification models to support frozen-section diagnosis within 30 minutes.

Authors

  • Jee Soo Park
    Department of Urology, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Soo Beom Choi
    Department of Medical Engineering, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Hee Jung Kim
  • Nam Hoon Cho
    Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea. cho1988@yuhs.ac.
  • Sang Wun Kim
    Department of Obstetrics and Gynecology, Institute of Women's Medical Life Science, Yonsei University College of Medicine, Seoul, Korea.
  • Young Tae Kim
    Department of Obstetrics and Gynecology, Institute of Women's Medical Life Science, Yonsei University College of Medicine, Seoul, Korea. ytkchoi@yuhs.ac.
  • Eun Ji Nam
    Department of Obstetrics and Gynecology, Institute of Women's Medical Life Science, Yonsei University College of Medicine, Seoul, Korea.
  • Jai Won Chung
  • Deok Won Kim
    Department of Medical Engineering, Yonsei University College of Medicine, Seoul, Republic of Korea.

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