Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data
المؤلفون المشاركون
Kawaguchi, Atsushi
Tsuruya, Kazuhiko
Yoshida, Hisako
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-05-13
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص EN
Magnetic resonance imaging (MRI) data is an invaluable tool in brain morphology research.
Here, we propose a novel statistical method for investigating the relationship between clinical characteristics and brain morphology based on three-dimensional MRI data via radial basis function-sparse partial least squares (RBF-sPLS).
Our data consisted of MRI image intensities for multimillion voxels in a 3D array along with 73 clinical variables.
This dataset represents a suitable application of RBF-sPLS because of a potential correlation among voxels as well as among clinical characteristics.
Additionally, this method can simultaneously select both effective brain regions and clinical characteristics based on sparse modeling.
This is in contrast to existing methods, which consider prespecified brain regions because of the computational difficulties involved in processing high-dimensional data.
RBF-sPLS employs dimensionality reduction in order to overcome this obstacle.
We have applied RBF-sPLS to a real dataset composed of 102 chronic kidney disease patients, while a comparison study used a simulated dataset.
RBF-sPLS identified two brain regions of interest from our patient data: the temporal lobe and the occipital lobe, which are associated with aging and anemia, respectively.
Our simulation study suggested that such brain regions are extracted with excellent accuracy using our method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yoshida, Hisako& Kawaguchi, Atsushi& Tsuruya, Kazuhiko. 2013. Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-483304
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yoshida, Hisako…[et al.]. Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-483304
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yoshida, Hisako& Kawaguchi, Atsushi& Tsuruya, Kazuhiko. Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-483304
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-483304
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر