Ovarian torsion: developing a machine-learned algorithm for diagnosis

被引：0
|
作者：
Jeffrey P. Otjen
A. Luana Stanescu
Adam M. Alessio
Marguerite T. Parisi
机构：
[1] Seattle Children’s Hospital and the University of Washington,Department of Radiology
[2] Seattle Children’s Hospital,Computational Mathematics, Science, and Engineering (CMSE), Biomedical Engineering (BME) and Radiology, Institute for Quantitative Health Science & Engineering (IQ)
[3] Michigan State University,undefined
来源：
Pediatric Radiology | 2020年 / 50卷
关键词：
Algorithm; Children; Machine learning; Medialization; Ovary; Torsion; Ultrasound;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：706 / 714
页数：8
相关论文
共 50 条
  • [21] A Genetic Algorithm Trained Machine-Learned Interatomic Potential for the Silicon-Carbon System
    MacIsaac, Michael
    Bavdekar, Salil
    Spearot, Douglas
    Subhash, Ghatu
    [J]. JOURNAL OF PHYSICAL CHEMISTRY C, 2024, 128 (29): : 12213 - 12226
  • [22] Machine-Learned Classifiers for Protocol Selection on a Shared Network
    Anvari, Hamidreza
    Huard, Jesse
    Lu, Paul
    [J]. MACHINE LEARNING FOR NETWORKING, 2019, 11407 : 98 - 116
  • [23] Machine-learned contours to assist boundary tracing tasks
    Crawford-Hines, S
    Anderson, C
    [J]. 1998 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION, 1998, : 229 - 231
  • [24] Bayesian uncertainty quantification for machine-learned models in physics
    Gal, Yarin
    Koumoutsakos, Petros
    Lanusse, Francois
    Louppe, Gilles
    Papadimitriou, Costas
    [J]. NATURE REVIEWS PHYSICS, 2022, 4 (09) : 573 - 577
  • [25] The adaptation of a machine-learned sentence realization system to French
    Smets, M
    Gamon, M
    Corston-Oliver, S
    Ringger, E
    [J]. EACL 2003: 10TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, PROCEEDINGS OF THE CONFERENCE, 2003, : 323 - 330
  • [26] Machine-learned Regularization and Polygonization of Building Segmentation Masks
    Zorzi, Stefano
    Bittner, Ksenia
    Fraundorfer, Friedrich
    [J]. 2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2021, : 3098 - 3105
  • [27] Bayesian uncertainty quantification for machine-learned models in physics
    Yarin Gal
    Petros Koumoutsakos
    Francois Lanusse
    Gilles Louppe
    Costas Papadimitriou
    [J]. Nature Reviews Physics, 2022, 4 : 573 - 577
  • [28] IMPROVING CFD SIMULATIONS BY LOCAL MACHINE-LEARNED CORRECTIONS
    Mitra, Peetak
    Haghshenas, Majid
    Dal Santo, Niccolo
    Daly, Conor
    Schmidt, David P.
    [J]. PROCEEDINGS OF ASME 2023 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, IMECE2023, VOL 9, 2023,
  • [29] Generating a Machine-Learned Equation of State for Fluid Properties
    Zhu, Kezheng
    Muller, Erich A.
    [J]. JOURNAL OF PHYSICAL CHEMISTRY B, 2020, 124 (39): : 8628 - 8639
  • [30] Machine-learned approximations to Density Functional Theory Hamiltonians
    Hegde, Ganesh
    Bowen, R. Chris
    [J]. SCIENTIFIC REPORTS, 2017, 7
12345