Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma

被引:0
|
作者
Hyung Min Kim
Seok-Soo Byun
Jung Kwon Kim
Chang Wook Jeong
Cheol Kwak
Eu Chang Hwang
Seok Ho Kang
Jinsoo Chung
Yong-June Kim
Yun-Sok Ha
Sung-Hoo Hong
机构
[1] The Catholic University of Korea,Department of Medical Informatics, College of Medicine
[2] The Catholic University of Korea,Department of Biomedicine and Health Sciences, College of Medicine
[3] Seoul National University Bundang Hospital,Department of Urology, Seoul National University College of Medicine
[4] Seoul National University Hospital,Department of Urology, Seoul National University College of Medicine
[5] Chonnam National University Medical School,Department of Urology
[6] Korea University School of Medicine,Department of Urology
[7] National Cancer Center,Department of Urology
[8] Chungbuk National University College of Medicine,Department of Urology
[9] Chungbuk National University,Department of Urology, College of Medicine
[10] Kyungpook National University,Department of Urology, Kyungpook National University Chilgok Hospital, School of Medicine
[11] The Catholic University,Department of Urology, Seoul St. Mary’s Hospital, College of Medicine
关键词
Renal cell carcinoma; Machine learning; ROC curve: KOrean Renal Cell Carcinoma; Late recurrence;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [21] Machine learning-based prediction model for hypofibrinogenemia after tigecycline therapy
    Zhu, Jianping
    Zhao, Rui
    Yu, Zhenwei
    Li, Liucheng
    Wei, Jiayue
    Guan, Yan
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2024, 24 (01)
  • [22] Machine learning-based histological classification that predicts recurrence of lung squamous cell carcinoma
    Koike, Yutaro
    Aokage, Keiju
    Ikeda, Kosuke
    Nakai, Tokiko
    Tane, Kenta
    Miyoshi, Tomohiro
    Sugano, Masato
    Kojima, Motohiro
    Fujii, Satoshi
    Kuwata, Takeshi
    Ochiai, Atsushi
    Tanaka, Toshiyuki
    Suzuki, Kenji
    Tsuboi, Masahiro
    Ishii, Genichiro
    CANCER SCIENCE, 2021, 112 : 882 - 882
  • [23] Recurrence prediction in clear cell renal cell carcinoma using machine learning of quantitative nuclear features
    Shuya Matsubara
    Akira Saito
    Naoto Tokuyama
    Ryu Muraoka
    Takeshi Hashimoto
    Naoya Satake
    Toshitaka Nagao
    Masahiko Kuroda
    Yoshio Ohno
    Scientific Reports, 13
  • [24] Recurrence prediction in clear cell renal cell carcinoma using machine learning of quantitative nuclear features
    Matsubara, Shuya
    Saito, Akira
    Tokuyama, Naoto
    Muraoka, Ryu
    Hashimoto, Takeshi
    Satake, Naoya
    Nagao, Toshitaka
    Kuroda, Masahiko
    Ohno, Yoshio
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [25] Machine learning-based prediction of survival prognosis in esophageal squamous cell carcinoma
    Zhang, Kaijiong
    Ye, Bo
    Wu, Lichun
    Ni, Sujiao
    Li, Yang
    Wang, Qifeng
    Zhang, Peng
    Wang, Dongsheng
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [26] Machine learning-based survival prediction model for postoperative parotid mucoepidermoid carcinoma
    Zihan, C.
    Ying, L.
    Zongwei, H.
    Sufang, Q.
    ANNALS OF ONCOLOGY, 2023, 34 : S578 - S578
  • [27] Machine learning-based radiomics models for prediction of locoregional recurrence in patients with breast cancer
    Lee, Joongyo
    Yoo, Sang Kyun
    Kim, Kangpyo
    Lee, Byung Min
    Park, Vivian Youngjean
    Kim, Jin Sung
    Kim, Yong Bae
    ONCOLOGY LETTERS, 2023, 26 (04)
  • [28] MACHINE LEARNING TO PREDICT RECURRENCE OF LOCALIZED RENAL CELL CARCINOMA
    Guo, Yanbo
    Braga, Luis
    Kapoor, Anil
    JOURNAL OF UROLOGY, 2019, 201 (04): : E145 - E145
  • [29] LATE RECURRENCE OF RENAL-CELL CARCINOMA AFTER NEPHRECTOMY
    NAKANO, E
    FUJIOKA, H
    MATSUDA, M
    OSAFUNE, M
    TAKAHA, M
    SONODA, T
    EUROPEAN UROLOGY, 1984, 10 (05) : 347 - 349
  • [30] Machine learning-based prognostic model for patients with anaplastic thyroid carcinoma
    Sun, Yihan
    Lin, Da
    Deng, Xiangyang
    Zhang, Yinlong
    DISCOVER ONCOLOGY, 2025, 16 (01)