Konferans bildirisi Açık Erişim

Multi-modal Brain Tensor Factorization: Preliminary Results with AD Patients

Durusoy, Goktekin; Karaaslanli, Abdullah; Dal, Demet Yuksel; Yildirim, Zerrin; Acar, Burak


MARC21 XML

<?xml version='1.0' encoding='UTF-8'?>
<record xmlns="http://www.loc.gov/MARC21/slim">
  <leader>00000nam##2200000uu#4500</leader>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">Multi-modal Brain Tensor Factorization: Preliminary Results with AD Patients</subfield>
  </datafield>
  <datafield tag="024" ind1=" " ind2=" ">
    <subfield code="a">10.1007/978-3-030-00755-3_4</subfield>
    <subfield code="2">doi</subfield>
  </datafield>
  <controlfield tag="001">110358</controlfield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">user-tubitak-destekli-proje-yayinlari</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">Global brain network parameters suffer from low classification performance and fail to provide an insight into the neurodegenerative diseases. Besides, the variability in connectivity definitions poses a challenge. We propose to represent multi-modal brain networks over a population with a single 4D brain tensor (B) and factorize B to get a lower dimensional representation per case and per modality. We used 7 known functional networks as the canonical network space to get a 7D representation. In a preliminary study over a group of 20 cases, we assessed this representation for classification. We used 6 different connectivity definitions (modalities). Linear discriminant analysis results in 90-95% accuracy in binary classification. The assessment of the canonical coordinates reveals Salience subnetwork to be the most powerful in classification consistently over all connectivity definitions. The method can be extended to include functional networks and further be used to search for discriminating subnetworks.</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="7">
    <subfield code="2">opendefinition.org</subfield>
    <subfield code="a">cc-by</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Bogazici Univ, VAVlab, Dept Elect &amp; Elect Engn, Istanbul, Turkey</subfield>
    <subfield code="a">Karaaslanli, Abdullah</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Bogazici Univ, VAVlab, Dept Elect &amp; Elect Engn, Istanbul, Turkey</subfield>
    <subfield code="a">Dal, Demet Yuksel</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Istanbul Univ, Dept Neurosci, Aziz Sancar Expt Med Res Inst, Istanbul, Turkey</subfield>
    <subfield code="a">Yildirim, Zerrin</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Bogazici Univ, VAVlab, Dept Elect &amp; Elect Engn, Istanbul, Turkey</subfield>
    <subfield code="a">Acar, Burak</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="b">conferencepaper</subfield>
    <subfield code="a">publication</subfield>
  </datafield>
  <datafield tag="542" ind1=" " ind2=" ">
    <subfield code="l">open</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="u">Bogazici Univ, VAVlab, Dept Elect &amp; Elect Engn, Istanbul, Turkey</subfield>
    <subfield code="a">Durusoy, Goktekin</subfield>
  </datafield>
  <datafield tag="711" ind1=" " ind2=" ">
    <subfield code="a">CONNECTOMICS IN NEUROIMAGING, CNI 2018</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2018-01-01</subfield>
  </datafield>
  <controlfield tag="005">20210420140645.0</controlfield>
  <datafield tag="909" ind1="C" ind2="O">
    <subfield code="o">oai:zenodo.org:110358</subfield>
    <subfield code="p">user-tubitak-destekli-proje-yayinlari</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="z">md5:75c514a207a3bf0e8aad406bbad22269</subfield>
    <subfield code="s">187</subfield>
    <subfield code="u">https://aperta.ulakbim.gov.trrecord/110358/files/bib-4ff0af40-3aad-4a1f-afa5-54a7d1f5d752.txt</subfield>
  </datafield>
  <datafield tag="540" ind1=" " ind2=" ">
    <subfield code="u">http://www.opendefinition.org/licenses/cc-by</subfield>
    <subfield code="a">Creative Commons Attribution</subfield>
  </datafield>
</record>
31
11
görüntülenme
indirilme
Görüntülenme 31
İndirme 11
Veri hacmi 2.1 kB
Tekil görüntülenme 31
Tekil indirme 11

Alıntı yap