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  <doi_batch_id>aspg-21-1291-1791472316</doi_batch_id>
  <timestamp>20261008151156</timestamp>
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  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Neutrosophic Science</full_title>
    <abbrev_title>IJNS</abbrev_title>
    <issn media_type="print">2692-6148</issn>
    <issn media_type="electronic">2690-6805</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <journal_volume>
     <volume>19</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>New Entropy Measure Concept for Single Value Neutrosophic Sets with Application in Medical Diagnosis</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Norzieha</given_name>
      <surname>Mustapha</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Kelantan, Machang Campus, Kelantan, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Suriana</given_name>
      <surname>Alias</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Kelantan, Machang Campus, Kelantan, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Roliza Md</given_name>
      <surname>Yasin</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Kelantan, Machang Campus, Kelantan, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Nurnisa Nasuha Mohd</given_name>
      <surname>Yusof</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Kelantan, Machang Campus, Kelantan, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Nurul Najiha</given_name>
      <surname>Fakhrarazi</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Kelantan, Machang Campus, Kelantan, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Nik Nur Aisyah Nik</given_name>
      <surname>Hassan</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Kelantan, Machang Campus, Kelantan, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>This study aims to propose a new entropy weight on the distance measure of single value neutrosophic set</jats:p>
     <jats:p>(SVNS) to analyse medical diagnosis patient’s risk. Four distance measures will be integrated with three</jats:p>
     <jats:p>entropy weight concepts and applied to medical diagnosis. A new entropy weight measure integrated with</jats:p>
     <jats:p>the four distance measures are calculated using the medical data of one patient with five symptoms and five</jats:p>
     <jats:p>diseases. The calculated new entropy and its associated distance measures give consistent finding with the</jats:p>
     <jats:p>existing entropy weight measures. However, all the values are even smaller showing that the relation between</jats:p>
     <jats:p>patient A and disease are stronger. This evaluation and diagnosis approach is applicable to a wide variety of</jats:p>
     <jats:p>other resources and medical problems.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>375</first_page>
     <last_page>383</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1291</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/IJNS.190118</doi>
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