Machine learning application with quantitative digital subtraction angiography for detection of hemorrhagic brain arteriovenous malformations

HIGHLIGHTS

  • who: JIA-SHENG HONG and collaborators from the Department of Biomedical Imaging and Radiological Sciences, National University, Taipei, Taiwan have published the article: Machine Learning Application With Quantitative Digital Subtraction Angiography for Detection of Hemorrhagic Brain Arteriovenous Malformations, in the Journal: (JOURNAL)
  • what: The authors aimed to detect the ruptured BAVMs by using QDSA features and machine_learning algorithms. A total of 150 cases were used in the data set used to train the models, and a separate data set comprising 21 cases was used for testing. H. STUDY LIMITATIONS Despite the favorable outcomes, this study . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?