Abstract
Alzheimer’s disease (AD) is considered to one of 10 key diseases leading to death in humans. AD is considered the main cause of brain degeneration, and will lead to dementia. It is beneficial for affected patients to be diagnosed with the disease at an early stage so that efforts to manage the patient can begin as soon as possible. Most existing protocols diagnose AD by way of magnetic resonance imaging (MRI). However, because the size of the images produced is large, existing techniques that employ MRI technology are expensive and time-consuming to perform. With this in mind, in the current study, AD is predicted instead by the use of a support vector machine (SVM) method based on gene-coding protein sequence information. In our proposed method, the frequency of two consecutive amino acids is used to describe the sequence information. The accuracy of the proposed method for identifying AD is 85.7%, which is demonstrated by the obtained experimental results. The experimental results also show that the sequence information of gene-coding proteins can be used to predict AD.
Highlights
Prior research has shown that there were more than 26.6 million people with Alzheimer’s disease (AD) worldwide in 2010 [1]
The experimental results show that the classification accuracy for AD prediction is 85.7%
A computational method based on protein sequence information was introduced to predict the onset of AD
Summary
Prior research has shown that there were more than 26.6 million people with AD worldwide in 2010 [1]. It has been predicted that there will soon be a further significant increase in prevalence: it is expected that there will be 70 million people with AD in 2030 and more than 115 million people with AD in 2050, respectively. In 2050, one in 85 people are expected to have AD. To date, there is no treatment in existence that can cure AD. The neurons of AD patients are destroyed gradually, resulting in the loss of cognitive ability and death. It is important to identify AD, an age-related disease [2], as early as possible so as to manage the advancement of the condition
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