ESTABLISHMENT OF NON-INVASIVE PREDICTION MODELS FOR DIAGNOSIS OF SUBTYPES AND COLLAGEN CONTENT OF UTERINE LEIOMYOMAS BY MACHINE LEARNING USING MRI DATA

被引：0
|
作者：
Tamehisa, Tetsuro [1 ]
Sato, Shun [1 ]
Tamura, Isao [1 ]
Sugino, Norihiro [1 ]
机构：
[1] Yamaguchi Univ, Grad Sch Med, Ube, Yamaguchi, Japan
来源：
FERTILITY AND STERILITY | 2024年 / 122卷 / 04期
关键词：
D O I：
暂无
中图分类号：
R71 [妇产科学];
学科分类号：
100211 ;
摘要：
P-664
引用
收藏
页码：E393 / E393
页数：1
相关论文
共 50 条
  • [31] Non-Invasive Ventilation Failure in Pediatric ICU: A Machine Learning Driven Prediction
    Chiaruttini, Maria Vittoria
    Lorenzoni, Giulia
    Daverio, Marco
    Marchetto, Luca
    Izzo, Francesca
    Chidini, Giovanna
    Picconi, Enzo
    Nettuno, Claudio
    Zanonato, Elisa
    Sagredini, Raffaella
    Rossetti, Emanuele
    Mondardini, Maria Cristina
    Cecchetti, Corrado
    Vitale, Pasquale
    Alaimo, Nicola
    Colosimo, Denise
    Sacco, Francesco
    Genoni, Giulia
    Perrotta, Daniela
    Micalizzi, Camilla
    Moggia, Silvia
    Chisari, Giosue
    Rulli, Immacolata
    Wolfler, Andrea
    Amigoni, Angela
    Gregori, Dario
    DIAGNOSTICS, 2024, 14 (24)
  • [32] NOVEL MACHINE LEARNING APPROACHES TO THE NON-INVASIVE DIAGNOSIS OF LIVER FIBROSIS IN NAFLD
    Kim, W. Ray
    Liang, Jane
    Mannalithara, Ajitha
    Charu, Vivek
    GASTROENTEROLOGY, 2023, 164 (06) : S1246 - S1247
  • [33] Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition
    Linka, K.
    Thuering, J.
    Rieppo, L.
    Aydin, R. C.
    Cyron, C. J.
    Kuhl, C.
    Merhof, D.
    Truhn, D.
    Nebelung, S.
    OSTEOARTHRITIS AND CARTILAGE, 2021, 29 (04) : 592 - 602
  • [34] A machine learning approach for non-invasive fall detection using Kinect
    Mahrukh Mansoor
    Rashid Amin
    Zaid Mustafa
    Sudhakar Sengan
    Hamza Aldabbas
    Mafawez T. Alharbi
    Multimedia Tools and Applications, 2022, 81 : 15491 - 15519
  • [35] Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms
    Victor, Odeh Adeyi
    Chen, Yifan
    Ding, Xiaorong
    SENSORS, 2024, 24 (07)
  • [36] Estimation of Intracranial Pressure Using Non-Invasive Monitor and Machine Learning
    Habboub, Ghaith
    Hassett, Catherine
    Kondylis, Efstathios
    Gomes, Joao
    NEUROSURGERY, 2023, 69 : 73 - 74
  • [37] Non-invasive phenotyping of hepatic fibrosis using unsupervised machine learning
    Brag, J.
    Nakano, Y.
    Cabrera-Lozoya, R.
    Oubel, E.
    Wagner, M.
    Lucidarme, O.
    JOURNAL OF HEPATOLOGY, 2018, 68 : S396 - S396
  • [38] A machine learning approach for non-invasive fall detection using Kinect
    Mansoor, Mahrukh
    Amin, Rashid
    Mustafa, Zaid
    Sengan, Sudhakar
    Aldabbas, Hamza
    Alharbi, Mafawez T.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (11) : 15491 - 15519
  • [39] Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data
    Eshaghi, Arman
    Young, Alexandra L.
    Wijeratne, Peter A.
    Prados, Ferran
    Arnold, Douglas L.
    Narayanan, Sridar
    Guttmann, Charles R. G.
    Barkhof, Frederik
    Alexander, Daniel C.
    Thompson, Alan J.
    Chard, Declan
    Ciccarelli, Olga
    NATURE COMMUNICATIONS, 2021, 12 (01)
  • [40] Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches
    Yin, Peng-Nien
    Kishan, K. C.
    Wei, Shishi
    Yu, Qi
    Li, Rui
    Haake, Anne R.
    Miyamoto, Hiroshi
    Cui, Feng
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2020, 20 (01)
12345