Editorial for "Development and Validation of a Combined MRI Radiomics, Imaging and Clinical Parameter Based Machine Learning Model for Identifying Idiopathic Central Precocious Puberty in Girls"

被引:3
|
作者
Peper, Eva S. [1 ]
Bastiaansen, Jessica A. M.
机构
[1] Univ Bern, Bern Univ Hosp, Dept Diagnost Intervent & Pediat Radiol DIPR, Inselspital, Bern, Switzerland
关键词
D O I
10.1002/jmri.28728
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
引用
收藏
页码:1988 / 1989
页数:2
相关论文
共 50 条
  • [1] Development and Validation of Clinical Diagnostic Model for Girls with Central Precocious Puberty: Machine-learning Approaches
    Quynh Thi Vu Huynh
    Nguyen Quoc Khanh Le
    Huang, Shih-Yi
    Ban Tran Ho
    Tru Huy Vu
    Hong Thi Minh Pham
    An Le Pham
    Hou, Jia-Woei
    Ngan Thi Kim Nguyen
    Chen, Yang Ching
    PLOS ONE, 2022, 17 (01):
  • [2] Development and validation of central precocious puberty diagnostic prediction models in girls based on machine learning
    Wu, Wenyong
    Chen, Ruimin
    HORMONE RESEARCH IN PAEDIATRICS, 2024, 97 : 522 - 522
  • [3] Development and validation of a model for predicting the adult height of girls with idiopathic central precocious puberty
    Wenyong Wu
    Xiaoyun Zhu
    Yun Chen
    Xiaohong Yang
    Ying Zhang
    Ruimin Chen
    European Journal of Pediatrics, 2023, 182 : 1627 - 1635
  • [4] Development and validation of a model for predicting the adult height of girls with idiopathic central precocious puberty
    Wu, Wenyong
    Zhu, Xiaoyun
    Chen, Yun
    Yang, Xiaohong
    Zhang, Ying
    Chen, Ruimin
    EUROPEAN JOURNAL OF PEDIATRICS, 2023, 182 (04) : 1627 - 1635
  • [5] Noninvasive radiomics-based method for evaluating idiopathic central precocious puberty in girls
    Jiang, Hongyang
    Shu, Zhenyu
    Luo, Xiaoming
    Wu, Meizhen
    Wang, Mei
    Feng, Qi
    Chen, Junfa
    Lin, Chunmiao
    Ding, Zhongxiang
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2021, 49 (02)
  • [6] Machine learning identifies girls with central precocious puberty based on multisource data
    Pan, Liyan
    Liu, Guangjian
    Mao, Xiaojian
    Liang, Huiying
    JAMIA OPEN, 2020, 3 (04) : 567 - 575
  • [7] A mathematical model for predicting the adult height of girls with idiopathic central precocious puberty: A European validation
    Lemaire, Pierre
    de Benaze, Gwenaelle Duhil
    Mul, Dick
    Heger, Sabine
    Oostdijk, Wilma
    Brauner, Raja
    PLOS ONE, 2018, 13 (10):
  • [8] Development of Prediction Models Using Machine Learning Algorithms for Girls with Suspected Central Precocious Puberty: Retrospective Study
    Pan, Liyan
    Liu, Guangjian
    Mao, Xiaojian
    Li, Huixian
    Zhang, Jiexin
    Liang, Huiying
    Li, Xiuzhen
    JMIR MEDICAL INFORMATICS, 2019, 7 (01)
  • [9] A normative modelling approach based on brain charts to explore cortical development patterns in girls with idiopathic central precocious puberty
    Zhu, Xiangwen
    Mu, Yuzhu
    Luo, Chongjing
    Gong, Zhuqing
    Ge, Xiuhong
    Zhang, Qi
    Ding, Zhongxiang
    CHINESE SCIENCE BULLETIN-CHINESE, 2024, 69 (24): : 3589 - 3596
  • [10] Meta-analysis of machine learning models for the diagnosis of central precocious puberty based on clinical, hormonal (laboratory) and imaging data
    Chen, Yilin
    Huang, Xueqin
    Tian, Lu
    FRONTIERS IN ENDOCRINOLOGY, 2024, 15