Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Sep 18, 2019

Abstract

BACKGROUND: As artificial intelligence methods for the diagnosis of disease advance, we aimed to evaluate machine learning in the predictive task of distinguishing between malignant and benign breast lesions on an independent clinical magnetic resonance imaging (MRI) dataset within a single institution for subsequent use as a computer aid for radiologists.

Authors

  • Yu Ji
    Jiangxi Medical College, The First Affiliated Hospital, Nanchang University, Nanchang, China.
  • Hui Li
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Alexandra V Edwards
    Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC2026, Chicago, IL, 60637, USA.
  • John Papaioannou
    Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC2026, Chicago, IL, 60637, USA.
  • Wenjuan Ma
    Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China. Electronic address: mawenjuan2008@163.com.
  • Peifang Liu
    Department of Neurology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Maryellen L Giger
    Department of Radiology, University of Chicago, 5841 S Maryland Ave., Chicago, IL, 60637, USA.

Keywords

External Resources

Popular Topics
Recent Journals