Abstract
With the aging of the population, China has a large population base. The number of people suffering from mild cognitive impairment has gradually increased and gradually turned to senile dementia. The probability of mild cognitive impairment in China is about 5–7%, and about 15 million people are ill. To better distinguish mild cognitive impairment from Alzheimer’s, this paper adopted the machine learning (ML) method to model. The evaluation table was established by considering the reaction time, education, background, memory, and other aspects of the patient. Machine learning has been applied in the fields of the Internet, finance, medicine, automation, biological science, etc. Through the machine learning support vector machine (SVM) and linear regression, the classification accuracy was compared. The results showed that the classification accuracy of SVM was 87.92% under the ML algorithm. It also showed that ML was more conducive to classification and recognition, which has played an important role in the identification of mild cognitive impairment in the current aging population.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Li, H. Identification of Mild Cognitive Impairment by Machine Learning Algorithm. Neural Comput & Applic 35, 25121–25130 (2023). https://doi.org/10.1007/s00521-023-08489-x
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DOI: https://doi.org/10.1007/s00521-023-08489-x