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The ExaMode Ontology (full version)

DENNIS DOSSO; GIANMARIA SILVELLO


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  <identifier identifierType="DOI">10.5281/zenodo.4081387</identifier>
  <creators>
    <creator>
      <creatorName>DENNIS DOSSO</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7307-4607</nameIdentifier>
      <affiliation>University of Padua</affiliation>
    </creator>
    <creator>
      <creatorName>GIANMARIA SILVELLO</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-4970-4554</nameIdentifier>
      <affiliation>University of Padua</affiliation>
    </creator>
  </creators>
  <titles>
    <title>The ExaMode Ontology (full version)</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Ontology</subject>
    <subject>Colon Cancer</subject>
    <subject>ExaMode</subject>
    <subject>Digital Pathology</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-10-12</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4081387</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3907399</relatedIdentifier>
  </relatedIdentifiers>
  <version>0.4</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/1.0/legalcode">Creative Commons Attribution 1.0 Generic</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The goal of this document is to define an OWL 2 ontology for the ExaMode project whose overall goal is to build predictive algorithms to help pathologists in the diagnosis of cancer cases. The starting point of ExaMode are medical diagnostic reports associated with WSIs of examined tissues.&lt;/p&gt;

&lt;p&gt;The present ontology models the diagnostic reports associated with a (series of) WSI and enable a structured encoding of the main concepts of a diagnosis. These concepts and their relations can be used to automatically annotate WSI as well as to do some reasoning over diagnostic reports about the cervix, colon and lung cancer, and celiac disease.&lt;/p&gt;

&lt;p&gt;The full documentation is available here:&amp;nbsp;http://examode.dei.unipd.it/ontology/&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/825292/">825292</awardNumber>
      <awardTitle>EXtreme-scale Analytics via Multimodal Ontology Discovery &amp; Enhancement</awardTitle>
    </fundingReference>
  </fundingReferences>
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