Repository logo
Communities & Collections
All of WIReDSpace
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Marumo, A.M."

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Thumbnail Image
    Item
    Brain tumor classification on magnetic resonance imaging(MRI) scans using deep learning
    (2022) Marumo, A.M.
    A brain tumor is formed when there is a development of aberrant cells in the brain. Early detection of brain tumors increases the patient’s chances of survival. This study proposes a Convolutional Neural Network(CNN) model or system that will automatically classify or detect brain tumors on MRI scans without the interference of radiologists or physicians. To make the proposed model trustworthy, integrated gradients and XRAI are built and evaluated. The CNN model achieved 90% accuracy, 82% sensitivity, 95% specificity, 82% precision, 79% Cohen’s kappa statistic, 79% Matthews correlation coefficient, and 77% Gini coefficient. The built classifier is best explained by integrated gradients. In the medical industry, integrated gradients haven’t been widely used as an explanation for deep learning models. This study demonstrates how integrated gradient can be used to interpret deep learning models in the medical area.

DSpace software copyright © 2002-2025 LYRASIS

  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify