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Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis
المؤلفون المشاركون
Cárdenas-Peña, David
Collazos-Huertas, Diego
Castellanos-Dominguez, German
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-04-11
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Dementia is a growing problem that affects elderly people worldwide.
More accurate evaluation of dementia diagnosis can help during the medical examination.
Several methods for computer-aided dementia diagnosis have been proposed using resonance imaging scans to discriminate between patients with Alzheimer’s disease (AD) or mild cognitive impairment (MCI) and healthy controls (NC).
Nonetheless, the computer-aided diagnosis is especially challenging because of the heterogeneous and intermediate nature of MCI.
We address the automated dementia diagnosis by introducing a novel supervised pretraining approach that takes advantage of the artificial neural network (ANN) for complex classification tasks.
The proposal initializes an ANN based on linear projections to achieve more discriminating spaces.
Such projections are estimated by maximizing the centered kernel alignment criterion that assesses the affinity between the resonance imaging data kernel matrix and the label target matrix.
As a result, the performed linear embedding allows accounting for features that contribute the most to the MCI class discrimination.
We compare the supervised pretraining approach to two unsupervised initialization methods (autoencoders and Principal Component Analysis) and against the best four performing classification methods of the 2014 CADDementia challenge.
As a result, our proposal outperforms all the baselines (7% of classification accuracy and area under the receiver-operating-characteristic curve) at the time it reduces the class biasing.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Cárdenas-Peña, David& Collazos-Huertas, Diego& Castellanos-Dominguez, German. 2016. Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1100238
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Cárdenas-Peña, David…[et al.]. Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1100238
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Cárdenas-Peña, David& Collazos-Huertas, Diego& Castellanos-Dominguez, German. Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1100238
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1100238
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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