<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns="http://purl.org/rss/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/16196">
    <title>Repository Collection: null</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/16196</link>
    <description />
    <items>
      <rdf:Seq>
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/59191" />
      </rdf:Seq>
    </items>
    <dc:date>2026-04-04T12:10:39Z</dc:date>
  </channel>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/59191">
    <title>METHOD AND DEVICE FOR PROVIDING INFORMATION FOR CANCER DIAGNOSIS BY USING EXTRACELLULAR VESICLES</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/59191</link>
    <description>Title: METHOD AND DEVICE FOR PROVIDING INFORMATION FOR CANCER DIAGNOSIS BY USING EXTRACELLULAR VESICLES
Author(s): 김해영; 구교권; 김영규; 김은주; 이윤희; 박수현
Abstract: This method utilizes machine learning on the basis of extracellular vesicles obtained through a liquid biopsy, so as to provide information necessary for efficient cancer diagnosis, and comprises: collecting learning data including surface characteristic images of extracellular vesicles extracted from cancer cells; using the learning data so as to construct an artificial intelligence diagnosis model; and deriving cancer-related disease information through the constructed artificial intelligence diagnosis model on the basis of surface characteristic data of extracellular vesicles to be diagnosed.</description>
  </item>
</rdf:RDF>

