Open AccessSurvey on Early Detection of Alzheimer's Disease using Different Types of Neural Network Architecture
Author(s) -
Deepthi Kamath,
Misba Firdose Fathima,
Kambhampati. Monica,
M.Eng. Ir. Hendra Kusuma
Publication year - 2021
Publication title -
international journal of artificial intelligence (batam)/international journal of artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2686-3251
pISSN - 2407-7275
DOI - 10.36079/lamintang.ijai-0801.217
Subject(s) - disease , neuroscience , medicine , artificial neural network , biological neural network , alzheimer's disease , computer science , psychology , pathology , machine learning
Alzheimer’s disease is a condition that leads to, progressive neurological brain disorder and destroys cells of the brain thereby causing an individual to lose their ability to continue daily activities and also hampers their mentality. Diagnostic symptoms are experienced by patients usually at later stages after irreversible neural damage occurs. Detection of AD is challenging because sometimes the signs that distinguish AD MRI data, can be found in MRI data of normal healthy brains of older people. Even though this disease is not completely curable, earlier detection can aid in promising treatment and prevent permanent damage to brain tissues. Age and genetics are the greatest risk factors for this disease. This paper presents the latest reports on AD detection based on different types of Neural Network Architectures.