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    <journal-meta>
      <journal-id journal-id-type="nlm-ta">REA Press</journal-id>
      <journal-id journal-id-type="publisher-id">Null</journal-id>
      <journal-title>REA Press</journal-title><issn pub-type="ppub">3042-0180</issn><issn pub-type="epub">3042-0180</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
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    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.22105/scfa.v1i1.29 </article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Neutrosophic set, Single valued neutrosophic set, Tan-log distance, Medical diagnosis.</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Enhancing Medical Diagnosis with Single Valued Neutrosophic Sets and Tan-Log Distance</article-title><subtitle>Enhancing Medical Diagnosis with Single Valued Neutrosophic Sets and Tan-Log Distance</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Radha</surname>
		<given-names>Narmadhagnanam</given-names>
	</name>
	<aff>P.G. & Research Department of Mathematics, Government Arts College (Autonomous), Kumbakonam, Tamil Nadu, India.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Samuel</surname>
		<given-names>A Edward </given-names>
	</name>
	<aff>P.G. & Research Department of Mathematics, Government Arts College (Autonomous), Kumbakonam, Tamil Nadu, India.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>03</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>25</day>
        <month>03</month>
        <year>2024</year>
      </pub-date>
      <volume>1</volume>
      <issue>6</issue>
      <permissions>
        <copyright-statement>© 2024 REA Press</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>Enhancing Medical Diagnosis with Single Valued Neutrosophic Sets and Tan-Log Distance</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Most diseases share a mix of common and unique traits, with distinct symptoms appearing at the onset. This paper proposes a method to establish relationships between illness classes and individuals with specific pathologies, aiding physicians in plausible diagnoses. We introduce the tan-log distance among single valued Neutrosophic Sets (NSs) and discuss its characteristics. This approach addresses uncertainties and shortcomings in current methods. The application of this method to medical diagnosis demonstrates its effectiveness in identifying illnesses. The previously mentioned approach's concept serves as a vital safeguard against uncertainties and shortcomings in the existing methods. To determine the sickness that a person is suffering, the application of medical diagnosis is discussed. The result of the diagnosis showed how effective the recommended course of action was.
		</p>
		</abstract>
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