NOVEL CLASSIFICATION OF PATIENTS WITH EPITHELIAL OVARIAN CANCER USING MACHINE LEARNING TECHNOLOGY

被引:0
|
作者
Paik, E. S. [1 ]
Park, J. Y. [2 ]
Kim, J. H. [1 ]
Kim, T. J. [1 ]
Choi, C. H. [1 ]
Kim, B. G. [1 ]
Bae, D. S. [1 ]
Seo, S. W. [3 ]
Lee, J. W. [1 ]
Jeong, S. Y. [1 ]
机构
[1] Samsung Med Ctr, Obstet & Gynecol, Seoul, South Korea
[2] Asan Med Ctr, Dept Obstet & Gynecol, Seoul, South Korea
[3] Samsung Adv Inst Hlth Sci & Technol, Samsung Med Ctr, Seoul, South Korea
关键词
D O I
暂无
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
IGCS8-0046
引用
收藏
页码:718 / 718
页数:1
相关论文
共 50 条
  • [1] Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods
    Paik, E. Sun
    Lee, Jeong-Won
    Park, Jeong-Yeol
    Kim, Ju-Hyun
    Kim, Mijung
    Kim, Tae-Joong
    Choi, Chet Hun
    Kim, Byoung-Gie
    Bae, Duk-Soo
    Seo, Sung Wook
    JOURNAL OF GYNECOLOGIC ONCOLOGY, 2019, 30 (04)
  • [2] Classification of delirium patients using machine learning technology
    Noh, Y. J.
    Lee, J. H.
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2020, 127 : 22 - 22
  • [3] MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods
    Klein, Oliver
    Kanter, Frederic
    Kulbe, Hagen
    Jank, Paul
    Denkert, Carsten
    Nebrich, Grit
    Schmitt, Wolfgang D.
    Wu, Zhiyang
    Kunze, Catarina A.
    Sehouli, Jalid
    Darb-Esfahani, Silvia
    Braicu, Ioana
    Lellmann, Jan
    Thiele, Herbert
    Taube, Eliane T.
    PROTEOMICS CLINICAL APPLICATIONS, 2019, 13 (01)
  • [4] Artificial intelligence-assisted classification of epithelial ovarian cancer patients using machine learning clustering to determine the rate of platinum sensitivity and disease recurrence
    Nakayama, John
    Pindzola, Grace
    Summerscales, Tiffany
    McGaughey, Michael
    GYNECOLOGIC ONCOLOGY, 2024, 190 : S198 - S199
  • [5] Developing a Prognostic Gene Panel of Epithelial Ovarian Cancer Patients by a Machine Learning Model
    Lu, Tzu-Pin
    Kuo, Kuan-Ting
    Chen, Ching-Hsuan
    Chang, Ming-Cheng
    Lin, Hsiu-Ping
    Hu, Yu-Hao
    Chiang, Ying-Cheng
    Cheng, Wen-Fang
    Chen, Chi-An
    CANCERS, 2019, 11 (02)
  • [6] Using machine learning to predict ovarian cancer
    Lu, Mingyang
    Fan, Zhenjiang
    Xu, Bin
    Chen, Lujun
    Zheng, Xiao
    Li, Jundong
    Znati, Taieb
    Mi, Qi
    Jiang, Jingting
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2020, 141
  • [7] A prognostic system for epithelial ovarian carcinomas using machine learning
    Grimley, Philip M.
    Liu, Zhenqiu
    Darcy, Kathleen M.
    Hueman, Matthew T.
    Wang, Huan
    Sheng, Li
    Henson, Donald E.
    Chen, Dechang
    ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA, 2021, 100 (08) : 1511 - 1519
  • [8] Ovarian Cancer Detection and Classification Using Machine Leaning
    Aditya, M. S.
    Amrita, I
    Kodipalli, Ashwini
    Martis, Roshan Joy
    2021 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, COMMUNICATION, COMPUTER TECHNOLOGIES AND OPTIMIZATION TECHNIQUES (ICEECCOT), 2021, : 279 - 282
  • [9] A Novel Ensemble Bagging Classification Method for Breast Cancer Classification Using Machine Learning Techniques
    Ponnaganti, Naga Deepti
    Anitha, Raju
    TRAITEMENT DU SIGNAL, 2022, 39 (01) : 229 - 237
  • [10] Skin cancer classification using machine learning
    Rodrigue Bogne Tchema
    Anastasis C. Polycarpou
    Marios Nestoros
    Multimedia Tools and Applications, 2025, 84 (6) : 3239 - 3256