A Survey on Early Detection and Classification of Alzheimer’s Disease Using Machine Learning and Deep Learning Techniques

Author(s)	Rashmi V, Sankhya N Nayak
Country	India
Abstract	Alzheimer’s disease is a disease that is caused due to depositions of protein around the brain cells. These depositions will distort the regular working of the brain, slowly making the patient unable to think, talk or even do regular chores. People of age more than 60 are prone to Alzheimer’s. This disease has several stages which finally leads to dementia. In this regard, early detection of Alzheimer’s can help doctors to properly treat and to delay the further protein depositions in the brain. In order to do so, many machine learning and deep learning techniques have been employed, out of which linear regression, decision trees, CNN and support vector machine are some of them to name. This paper provides a detailed review on dissimilar works proposed by different authors and also discusses the performance analysis of each proposed model.
Keywords	Alzheimer’s, Dementia, Support vector machine (SVM), CNN architecture.
Field	Computer Applications
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-09-06
Cite This	A Survey on Early Detection and Classification of Alzheimer’s Disease Using Machine Learning and Deep Learning Techniques - Rashmi V, Sankhya N Nayak - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27137
DOI	https://doi.org/10.36948/ijfmr.2024.v06i05.27137
Short DOI	https://doi.org/gwfgrr

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International Journal For Multidisciplinary Research