Abstract
Accurate analysis of Alzheimer’s Disease (AD) from healthy patients is a significant concern. The knowledge about the condition’s seriousness and formative dangers due to AD leads to take prudent steps before the permanent brain damage takes place. Lately, there has been incredible benefits of computer-aided diagnosis (CAD) which uses various machine learning (ML) techniques for assisting the medical staff for AD diagnosis. In this paper, we proposed a model based on support vector machine (SVM) and made a comparison with three other classification algorithms for predicting normal control (NC) patients from AD patients. Lastly, the performances of the different algorithms are compared, and results of the model clearly indicate that gives quality performance for NC and AD classification.
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Sharma, R., Goel, T., Murugan, R. (2022). Prediction of Alzheimer’s Disease Using Machine Learning Algorithm. In: Das, K.N., Das, D., Ray, A.K., Suganthan, P.N. (eds) Proceedings of the International Conference on Computational Intelligence and Sustainable Technologies. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-6893-7_2
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DOI: https://doi.org/10.1007/978-981-16-6893-7_2
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