Automatic discrimination analysis method of mild cognitive impairment based on support vector machine

Abstract

The invention relates to an automatic discrimination analysis method of mild cognitive impairment based on a support vector machine. According to the automatic discrimination analysis method of mild cognitive impairment based on the support vector machine, multiple detection index data including aresting state fMRI, structure MRI and neuropsychological examination data are used, and methods of Functional Connectivity (FC) analysis, Voxel-based Morphometry (VBM) analysis and Fiber Tractography are adopted to extract a resting state functional connectivity characteristic, a gray matter structure characteristic and a white matter fiber connectivity characteristic, reduction is conducted on the characteristics based on a rough set approach, and finally classifier construction is conducted on multimodal MRI data based on the SVM method, so that automatic discrimination analysis of mild cognitive impairment is achieved, diagnosis accuracy of mild cognitive impairment is improved, and the accuracy rate of the diagnosis in experimental data reaches more than 90 percent. The method can be applied to practical clinical diagnosis.

Description

technical field [0001] The invention relates to an automatic discrimination and analysis method for mild cognitive impairment based on a support vector machine, belonging to the technical field of disease diagnosis. Background technique [0002] Alzheimer's disease (AD) is a fatal neurodegenerative disease with a high incidence in the elderly population, but there is currently no effective treatment. Mild Cognitive Impairment (MCI) is considered to be a clinical state between normal aging and AD. Early recognition and diagnosis at the stage of mild cognitive impairment can help delay disease progression, improve symptoms, and improve quality of life. [0003] Some studies have initially explored the diagnosis of mild cognitive impairment based on Magnetic Resonance Imaging (MRI). However, most studies are based on groups of subjects, and it is difficult to achieve individual diagnosis of patients. In recent years, some studies have attempted to use pattern recognition met...

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Problems solved by technology

[0005]my country has entered the aging stage, and Alzheimer's disease seriously affects the life of the elderly. At present, there is no effective treatment method to improve the early stage of Alzheimer's disease. Diagnostic accuracy is critical for early diagnosis and early intervention, delaying disease progression in patients

[0006] found in the application of Magnetic Resonance Imaging (MRI) technology in the differential diagnosis of Alzheimer's disease that it is difficult to use general linear classifiers and single-mode MRI features can linearly distinguish mild cognitive impairment from healthy elderly people, and the discriminative effect (specificity, accuracy) is difficult to meet the requirements of clinical diagnosis

There is still no effective method to automatically identify patients with mild cognitive impairment

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