Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer’s Disease and Mild Cognitive Impairment
المؤلفون المشاركون
Zhou, Qi
Barker, Warren
Duara, Ranjan
Loewenstein, David A.
Goryawala, Mohammed
Adjouadi, Malek
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-05-25
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) are difficult to demarcate to assess the progression of AD.
This study presents a statistical framework on the basis of MRI volumes and neuropsychological scores.
A feature selection technique using backward stepwise linear regression together with linear discriminant analysis is designed to classify cognitive normal (CN) subjects, early MCI (EMCI), late MCI (LMCI), and AD subjects in an exhaustive two-group classification process.
Results show a dominance of the neuropsychological parameters like MMSE and RAVLT.
Cortical volumetric measures of the temporal, parietal, and cingulate regions are found to be significant classification factors.
Moreover, an asymmetrical distribution of the volumetric measures across hemispheres is seen for CN versus EMCI and EMCI versus AD, showing dominance of the right hemisphere; whereas CN versus LMCI and EMCI versus LMCI show dominance of the left hemisphere.
A 2-fold cross-validation showed an average accuracy of 93.9%, 90.8%, and 94.5%, for the CN versus AD, CN versus LMCI, and EMCI versus AD, respectively.
The accuracy for groups that are difficult to differentiate like EMCI versus LMCI was 73.6%.
With the inclusion of the neuropsychological scores, a significant improvement (24.59%) was obtained over using MRI measures alone.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Goryawala, Mohammed& Zhou, Qi& Barker, Warren& Loewenstein, David A.& Duara, Ranjan& Adjouadi, Malek. 2015. Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer’s Disease and Mild Cognitive Impairment. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1057771
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Goryawala, Mohammed…[et al.]. Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer’s Disease and Mild Cognitive Impairment. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1057771
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Goryawala, Mohammed& Zhou, Qi& Barker, Warren& Loewenstein, David A.& Duara, Ranjan& Adjouadi, Malek. Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer’s Disease and Mild Cognitive Impairment. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1057771
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1057771
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