کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
386348 660883 2011 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Diagnose the mild cognitive impairment by constructing Bayesian network with missing data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Diagnose the mild cognitive impairment by constructing Bayesian network with missing data
چکیده انگلیسی

Mild Cognitive Impairment (MCI) is thought to be the prodromal phase to Alzheimer’s disease (AD), which is the most common form of dementia and leads to irreversible neurogenerative damage of the brain. In order to further improve the diagnostic quality of the MCI, we developed a MCI expert system to address MCI’s prediction and inference question, consequently, assist the diagnosis of doctor. In this system, we mainly deal with following problems: (1) Estimate missing data in the experiment by utilizing mutual information and Newton interpolation. (2) Make certain the prior feature ordering in constructing Bayesian network. (3) Construct the Bayesian network (We term the algorithm as MNBN). The experimental results indicate that MNBN algorithm achieved better results than some existing methods in most instances. The mean square error comes to 0.0173 in the MCI experiment. Our results shed light on the potential application in MCI diagnosis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 1, January 2011, Pages 442–449
نویسندگان
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