English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

An improved image mining technique for brain tumor classification usingpruned association rule with MARI algorithm is presented in this paper. Themethod proposed makes use of association rule mining technique to classify theCT scan brain images into three categories namely normal, benign and malign. Itcombines the low level features extracted from images and high level knowledgefrom specialists. The developed algorithm can assist the physicians forefficient classification with multiple keywords per image to improve theaccuracy. The experimental result on prediagnosed database of brain imagesshowed 96 percent and 93 percent sensitivity and accuracy respectively.

An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier