Prediction of ovarian cancer with deep machine-learning and alternative splicing

被引：0
|
作者：
Watson, Rachel [1 ]
Ulmer, Keely [2 ]
Gabrilovich, Sofia [1 ]
Goodheart, Michael [1 ]
Bender, David [1 ]
McDonald, Megan [1 ]
Devor, Eric [1 ]
Bosquet, Jesus Gonzalez [1 ]
机构：
[1] Univ Iowa, Div Gynecol Oncol, Iowa City, IA USA
[2] Univ Iowa, Iowa City, IA USA
来源：
GYNECOLOGIC ONCOLOGY | 2023年 / 176卷
关键词：
D O I：
10.1016/j.ygyno.2023.06.289
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
2167
引用
收藏
页码：S236 / S236
页数：1
相关论文
共 50 条
  • [31] Machine-Learning Applications in Structural Response Prediction: A Review
    Afshar, Aref
    Nouri, Gholamreza
    Ghazvineh, Shahin
    Hosseini Lavassani, Seyed Hossein
    PRACTICE PERIODICAL ON STRUCTURAL DESIGN AND CONSTRUCTION, 2024, 29 (03)
  • [32] Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods
    Zheng, Suqing
    Wang, Yibing
    Liu, Hongmei
    Chang, Wenping
    Xu, Yong
    Lin, Fu
    CHEMICAL RESEARCH IN TOXICOLOGY, 2019, 32 (06) : 1014 - 1026
  • [33] Machine-learning techniques for the prediction of protein–protein interactions
    Debasree Sarkar
    Sudipto Saha
    Journal of Biosciences, 2019, 44
  • [34] Machine-learning models for prediction of sepsis patients mortality
    Bao, C.
    Deng, F.
    Zhao, S.
    MEDICINA INTENSIVA, 2023, 47 (06) : 315 - 325
  • [35] Energy landscapes for a machine-learning prediction of patient discharge
    Das, Ritankar
    Wales, David J.
    PHYSICAL REVIEW E, 2016, 93 (06)
  • [36] Performance Prediction of NUMA Placement: a Machine-Learning Approach
    Arapidis, Fanourios
    Karakostas, Vasileios
    Papadopoulou, Nikela
    Nikas, Konstantinos
    Goumas, Georgios
    Koziris, Nectarios
    2018 16TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM 2018), 2018, : 296 - 301
  • [37] Machine-learning methods for stream water temperature prediction
    Feigl, Moritz
    Lebiedzinski, Katharina
    Herrnegger, Mathew
    Schulz, Karsten
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2021, 25 (05) : 2951 - 2977
  • [38] Representation of compounds for machine-learning prediction of physical properties
    Seko, Atsuto
    Hayashi, Hiroyuki
    Nakayama, Keita
    Takahashi, Akira
    Tanaka, Isao
    PHYSICAL REVIEW B, 2017, 95 (14)
  • [39] Design of Machine-Learning Classifier for Stock Market Prediction
    Srivastava A.K.
    Srivastava A.
    Singh S.
    Sugandha S.
    Tripta
    Gupta S.
    SN Computer Science, 2022, 3 (1)
  • [40] A systematic review on machine learning and deep learning techniques in cancer survival prediction
    Deepa, P.
    Gunavathi, C.
    PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY, 2022, 174 : 62 - 71
12345