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  <doi_batch_id>aspg-21-1192-1791472160</doi_batch_id>
  <timestamp>20261008150920</timestamp>
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   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <registrant>American Scientific Publishing Group</registrant>
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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>18</volume>
    </journal_volume>
    <issue>4</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Diabetic Neuropathy Severity Assessment: A Neutrosophic approach</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>R.</given_name>
      <surname>Sundareswaran</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Mathematics, Sri Sivasubramaniya Nadar College of Engineering, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>V.</given_name>
      <surname>Mahesh</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Biomedical Engineering, Sri Sivasubramaniya Nadar College of Engineering, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Said</given_name>
      <surname>Broumi</surname>
      <affiliations>
       <institution>
        <institution_name>Laboratory of Information Processing, Faculty of Science Ben M’Sik, University Hassan II, B.P 7955, Sidi Othman, Casablanca, Morocco</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>R. Dhanush</given_name>
      <surname>Babu</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Biomedical Engineering, Sri Sivasubramaniya Nadar College of Engineering, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>M</given_name>
      <surname>Vahini</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Biomedical Engineering, Sri Sivasubramaniya Nadar College of Engineering, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>In this work a Neutrosophic approach has been implemented to assess the severity of diabetic neuropathy. Vibratory Perception Threshold (VPT) data was acquired from 600 participants. The acquired data was utilised to obtain the various criteria to assess the severity of diabetic neuropathy which is a fatal consequence of Diabetes mellitus. A single valued Neutrosophic set was employed to assess and evaluate the given medical condition. Multi Criteria Decision Making (MCDM) was used to address the severity. The hybrid score accuracy function and the collective correlation of the decision matrices were calculated and were used to estimate the weights which ultimately aided in the ranking process. The results corroborated that Grade II neuropathy is the most severe condition and needs more conscientious diagnosis.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>291</first_page>
     <last_page>300</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1192</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/IJNS.180424</doi>
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