Dataset Closed Access

Data publication: Multitask learning with convolutional neural networks and vision transformers can improve outcome prediction for head and neck cancer patients

Starke, Sebastian; Zwanenburg, Alex; Leger, Karoline; Lohaus, Fabian; Linge, Annett; Schreiber, Andreas; Kalinauskaite, Goda; Tinhofer, Inge; Guberina, Nika; Guberina, Maja; Balermpas, Panagiotis; von der Grün, Jens; Ganswindt, Ute; Belka, Claus; Peeken, Jan C.; Combs, Stephanie E.; Böke, Simon; Zips, Daniel; Richter, Christian; Troost, Esther Gera Cornelia; Krause, Mechthild; Baumann, Michael; Löck, Steffen

DataCite XML Export

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      <creatorName>Starke, Sebastian</creatorName>
      <givenName>Sebastian</givenName>
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    <creator>
      <creatorName>Zwanenburg, Alex</creatorName>
      <givenName>Alex</givenName>
      <familyName>Zwanenburg</familyName>
      <affiliation>National Center for Tumor Diseases (NCT)</affiliation>
    </creator>
    <creator>
      <creatorName>Leger, Karoline</creatorName>
      <givenName>Karoline</givenName>
      <familyName>Leger</familyName>
      <affiliation>Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus</affiliation>
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      <creatorName>Lohaus, Fabian</creatorName>
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      <creatorName>Linge, Annett</creatorName>
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      <affiliation>Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus</affiliation>
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    <creator>
      <creatorName>Schreiber, Andreas</creatorName>
      <givenName>Andreas</givenName>
      <familyName>Schreiber</familyName>
      <affiliation>Department of Radiotherapy, Hospital Dresden-Friedrichstadt</affiliation>
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      <creatorName>Kalinauskaite, Goda</creatorName>
      <givenName>Goda</givenName>
      <familyName>Kalinauskaite</familyName>
      <affiliation>Department of Radiooncology and Radiotherapy, Charité University Hospital</affiliation>
    </creator>
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      <creatorName>Tinhofer, Inge</creatorName>
      <givenName>Inge</givenName>
      <familyName>Tinhofer</familyName>
      <affiliation>Department of Radiooncology and Radiotherapy, Charité University Hospital</affiliation>
    </creator>
    <creator>
      <creatorName>Guberina, Nika</creatorName>
      <givenName>Nika</givenName>
      <familyName>Guberina</familyName>
      <affiliation>Department of Radiotherapy, Medical Faculty, University of Duisburg-Essen</affiliation>
    </creator>
    <creator>
      <creatorName>Guberina, Maja</creatorName>
      <givenName>Maja</givenName>
      <familyName>Guberina</familyName>
      <affiliation>Department of Radiotherapy, Medical Faculty, University of Duisburg-Essen</affiliation>
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      <creatorName>Balermpas, Panagiotis</creatorName>
      <givenName>Panagiotis</givenName>
      <familyName>Balermpas</familyName>
      <affiliation>Department of Radiotherapy and Oncology, Goethe-University Frankfurt</affiliation>
    </creator>
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      <creatorName>von der Grün, Jens</creatorName>
      <givenName>Jens</givenName>
      <familyName>von der Grün</familyName>
      <affiliation>Department of Radiotherapy and Oncology, Goethe-University Frankfurt</affiliation>
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      <creatorName>Ganswindt, Ute</creatorName>
      <givenName>Ute</givenName>
      <familyName>Ganswindt</familyName>
      <affiliation>Department of Radiation Oncology, Medical University of Innsbruck</affiliation>
    </creator>
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      <creatorName>Belka, Claus</creatorName>
      <givenName>Claus</givenName>
      <familyName>Belka</familyName>
      <affiliation>Department of Radiation Oncology, Ludwig-Maximilians-Universität</affiliation>
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    <creator>
      <creatorName>Peeken, Jan C.</creatorName>
      <givenName>Jan C.</givenName>
      <familyName>Peeken</familyName>
      <affiliation>Department of Radiation Oncology, Technische Universität München</affiliation>
    </creator>
    <creator>
      <creatorName>Combs, Stephanie E.</creatorName>
      <givenName>Stephanie E.</givenName>
      <familyName>Combs</familyName>
      <affiliation>Department of Radiation Oncology, Technische Universität München</affiliation>
    </creator>
    <creator>
      <creatorName>Böke, Simon</creatorName>
      <givenName>Simon</givenName>
      <familyName>Böke</familyName>
      <affiliation>Department of Radiation Oncology, Faculty of Medicine and University Hospital Tübingen</affiliation>
    </creator>
    <creator>
      <creatorName>Zips, Daniel</creatorName>
      <givenName>Daniel</givenName>
      <familyName>Zips</familyName>
      <affiliation>Department of Radiation Oncology, Faculty of Medicine and University Hospital Tübingen</affiliation>
    </creator>
    <creator>
      <creatorName>Richter, Christian</creatorName>
      <givenName>Christian</givenName>
      <familyName>Richter</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-4261-4214</nameIdentifier>
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    <creator>
      <creatorName>Troost, Esther Gera Cornelia</creatorName>
      <givenName>Esther Gera Cornelia</givenName>
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      <creatorName>Krause, Mechthild</creatorName>
      <givenName>Mechthild</givenName>
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    <creator>
      <creatorName>Baumann, Michael</creatorName>
      <givenName>Michael</givenName>
      <familyName>Baumann</familyName>
      <affiliation>German Cancer Research Center (DKFZ)</affiliation>
    </creator>
    <creator>
      <creatorName>Löck, Steffen</creatorName>
      <givenName>Steffen</givenName>
      <familyName>Löck</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-7017-3738</nameIdentifier>
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  <titles>
    <title>Data publication: Multitask learning with convolutional neural networks and vision transformers can improve outcome prediction for head and neck cancer patients</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2023</publicationYear>
  <subjects>
    <subject>survival analysis</subject>
    <subject>vision transformer</subject>
    <subject>convolutional neural network</subject>
    <subject>multitask learning</subject>
    <subject>tumor segmentation</subject>
    <subject>head and neck cancer</subject>
    <subject>Cox proportional hazards</subject>
    <subject>loco-regional control</subject>
    <subject>progression-free survival</subject>
    <subject>discrete-time survival models</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2023-08-16</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/2438</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsReferencedBy">10.3390/cancers15194897</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-37408</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-37388</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-39339</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.2437</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/oncoray</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/closedAccess">Closed Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This dataset contains the model checkpoints, predictions and performance metrics for the multitask neural networks presented in the corresponding manuscript.&lt;/p&gt;</description>
  </descriptions>
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Publication date:
August 16, 2023
DOI:
10.14278/rodare.2438

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Keyword(s):
survival analysis vision transformer convolutional neural network multitask learning tumor segmentation head and neck cancer Cox proportional hazards loco-regional control progression-free survival discrete-time survival models
Related identifiers:
Identical to:
https://www.hzdr.de/publications/Publ-37408
Referenced by:
10.3390/cancers15194897, https://www.hzdr.de/publications/Publ-37388, https://www.hzdr.de/publications/Publ-39339
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