کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
388510 660926 2011 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A parallel neural network approach to prediction of Parkinson’s Disease
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A parallel neural network approach to prediction of Parkinson’s Disease
چکیده انگلیسی

Recently the neural network based diagnosis of medical diseases has taken a great deal of attention. In this paper a parallel feed-forward neural network structure is used in the prediction of Parkinson’s Disease. The main idea of this paper is using more than a unique neural network to reduce the possibility of decision with error. The output of each neural network is evaluated by using a rule-based system for the final decision. Another important point in this paper is that during the training process, unlearned data of each neural network is collected and used in the training set of the next neural network. The designed parallel network system significantly increased the robustness of the prediction. A set of nine parallel neural networks yielded an improvement of 8.4% on the prediction of Parkinson’s Disease compared to a single unique network. Furthermore, it is demonstrated that the designed system, to some extent, deals with the problems of imbalanced data sets.

Research highlights
► A parallel neural network system is designed for prediction of Parkinson’s Disease.
► Vocal recordings are used as attributes in the prediction.
► Forward propagation of unlearned data increase the reliability of the system.
► The parallel design favours imbalanced class distributions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 10, 15 September 2011, Pages 12470–12474
نویسندگان
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