• Chiramel Riya Francis
• Arlene D'costa
• Prabhjyot Kaur Bamrah

Alzheimer’s disease (AD) is characterized by severe memory loss and cognitive impairment .It is the most common type of dementia, accounting for 60 percent to 80 percent of dementia cases. Even though no cure has been obtained for curing Alzheimer’s disease, accurate and early diagnosis of Alzheimer's disease (AD) plays a significant role in patient care, especially at the early stage, because the consciousness of the severity and the progression risks allows the patients to take prevention measures before irreversible brain damages are shaped. Alzheimer’s Disease is a disease occurring in different stages causing brain structure changes which can be measured by magnetic resonance imaging(MRI).Detection of Alzheimer’s is usually done with these variations in brain anatomical structures and features such as destruction of neurons in parts of the brain evolved in memory such as entorhinal cortex and hippocampus .It later affects areas in cerebral cortex responsible for language ,reasoning and social behavior .These structure changes captured by the MRI can be exploited for further AD detection and prediction using image classification tools ,like Convolutional neural network (CNN) for feature extraction.

Alzheimer’s disease, prediction, detection, deep learning , machine learning

"Alzheimer's disease detection and prediction:A survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.126-131, May-2019, Available :http://www.jetir.org/papers/JETIR1905022.pdf

"Alzheimer's disease detection and prediction:A survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp126-131, May-2019, Available at : http://www.jetir.org/papers/JETIR1905022.pdf