Unsupervised machine learning identifies predictive progression markers of IPF

被引:0
|
作者
Jeanny Pan
Johannes Hofmanninger
Karl-Heinz Nenning
Florian Prayer
Sebastian Röhrich
Nicola Sverzellati
Venerino Poletti
Sara Tomassetti
Michael Weber
Helmut Prosch
Georg Langs
机构
[1] Medical University of Vienna,Computational Imaging Research Lab, Department of Biomedical Imaging and Image
[2] Medical University of Vienna,guided Therapy
[3] University of Parma,Department of Biomedical Imaging and Image
[4] Morgagni-Pierantoni Hospital,guided Therapy
[5] Aarhus University Hospital,Unit “Scienze Radiologiche”, Department of Medicine and Surgery (DiMeC)
来源
European Radiology | 2023年 / 33卷
关键词
Idiopathic pulmonary fibrosis; Unsupervised machine learning; Tomography, X-ray computed;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:925 / 935
页数:10
相关论文
共 50 条
  • [11] IoT Device Identification Using Unsupervised Machine Learning
    Koball, Carson
    Rimal, Bhaskar P.
    Wang, Yong
    Salmen, Tyler
    Ford, Connor
    INFORMATION, 2023, 14 (06)
  • [12] Clustering Seismocardiographic Events using Unsupervised Machine Learning
    Gamage, Peshala T.
    Azad, Md Khurshidul.
    Taebi, Amirtaha
    Sandler, Richard H.
    Mansy, Hansen A.
    2018 IEEE SIGNAL PROCESSING IN MEDICINE AND BIOLOGY SYMPOSIUM (SPMB), 2018,
  • [13] Identifying Medicare Provider Fraud with Unsupervised Machine Learning
    Bauder, Richard A.
    da Rosa, Raquel C.
    Khoshgoftaar, Taghi M.
    2018 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IRI), 2018, : 285 - 292
  • [14] UNSUPERVISED MACHINE LEARNING: A WELL PLANNING TOOL FOR THE FUTURE
    Batruny, Peter
    Robinson, Tim
    PROCEEDINGS OF ASME 2022 41ST INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE & ARCTIC ENGINEERING, OMAE2022, VOL 10, 2022,
  • [15] The Use of Unsupervised Machine Learning for the Attenuation of Seismic Noise
    Kim, Sujeong
    Jun, Hyunggu
    GEOPHYSICS AND GEOPHYSICAL EXPLORATION, 2022, 25 (02): : 71 - 84
  • [16] Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool
    Celecia, Alimed
    Figueiredo, Karla
    Rodriguez, Carlos
    Vellasco, Marley
    Maldonado, Edwin
    Silva, Marco Aurelio
    Rodrigues, Anderson
    Nascimento, Renata
    Ourofino, Carla
    SENSORS, 2021, 21 (19)
  • [17] Predictive model for novel subtypes of patients undergoing lower extremity amputation for peripheral artery disease: An unsupervised machine learning study
    Ma, Yuanliang
    Zhang, Lin
    Li, Que
    Qin, Xiao
    HELIYON, 2024, 10 (15)
  • [18] Explainable Unsupervised Machine Learning for Cyber-Physical Systems
    Wickramasinghe, Chathurika S.
    Amarasinghe, Kasun
    Marino, Daniel L.
    Rieger, Craig
    Manic, Milos
    IEEE ACCESS, 2021, 9 : 131824 - 131843
  • [19] Melt Instability Identification Using Unsupervised Machine Learning Algorithms
    Gansen, Alex
    Hennicker, Julian
    Sill, Clemens
    Dheur, Jean
    Hale, Jack S. S.
    Baller, Jorg
    MACROMOLECULAR MATERIALS AND ENGINEERING, 2023, 308 (06)
  • [20] A Case Study of Spectrum Analysis Using Unsupervised Machine Learning
    Nagpure, Vaishali
    Vaccaro, Stephanie
    Hood, Cynthia
    2019 IEEE INTERNATIONAL SYMPOSIUM ON DYNAMIC SPECTRUM ACCESS NETWORKS (DYSPAN), 2019, : 153 - 154