17 Mayıs 2024 Kitap bölümü Kısıtlı Erişim

Abut,Serdar; Okut, Hayrettin

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  <identifier identifierType="DOI">10.48623/aperta.274319</identifier>
  <creators>
    <creator>
      <creatorName>Abut,Serdar</creatorName>
      <givenName>Serdar</givenName>
      <familyName>Abut</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-6617-6688</nameIdentifier>
      <affiliation>Department of Computer Engineering, Siirt University,</affiliation>
    </creator>
    <creator>
      <creatorName>Okut, Hayrettin</creatorName>
      <givenName>Hayrettin</givenName>
      <familyName>Okut</familyName>
      <affiliation>University of Kansas School of Medicine</affiliation>
    </creator>
  </creators>
  <titles>
    <title>The Importance Of Artificial Neural Networks In Decision Making For The Field Of Medicine</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2024</publicationYear>
  <subjects>
    <subject>Artificial neural network</subject>
    <subject>Convolutional neural network</subject>
    <subject>Deep learning</subject>
    <subject>Medical image processing</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2024-05-17</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Book section</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/274319</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.48623/aperta.274318</relatedIdentifier>
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  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/restrictedAccess">Restricted Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This book chapter explores the integration of machine learning techniques, particularly deep neural networks, in the field of medical image processing for precision medicine. The healthcare industry has accumulated vast amounts of complex data, and advancements in technology have led to an increase in structured and unstructured medical data. The chapter discusses the historical development of image processing techniques, moving from labor-intensive approaches to more efficient and faster operations using artificial neural networks. Various feature extraction methods, with a focus on dimensionality reduction, are investigated to optimize the performance of neural networks. The application of deep neural network models in medical imaging is explored, with a gradual implementation strategy proposed to address challenges related to data variability across institutions. The potential benefits and obstacles of using deep neural network models for psychiatric diagnoses and neonatal early detection are discussed. Throughout the chapter, the importance of effective communication between data scientists, software engineers, and clinicians is emphasized for the development of robust and practical artificial intelligence systems in healthcare. The overall viewpoint highlight how technological advancements in image processing have transformed artificial intelligence-based applications in the medical field and future developments can be looked at in a different light in this area.&lt;/p&gt;</description>
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