Open AccessAlzheimer's Disease Classification Using Deep CNN
Author(s) -
Shikha Agrawal,
Neha Sunil Pandharkar,
Pooja Arvind Khandelwal,
Pratiksha Ashok Pandhare,
Janhavi Sanjay Deoghare
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit217371
Subject(s) - dementia , disease , cognitive impairment , alzheimer's disease , medicine , cognition , psychology , pediatrics , psychiatry , pathology
Especially in the world, the deep learning algorithm has become a technique of choice for analyzing medical images rapidly. Alzheimer's disease (AD) is regarded to be the most prevalent cause of dementia, and only 1 in 4 individuals with Alzheimer's are estimated to be diagnosed correctly on time. However, there is no refractory available treatment, the disorders can be managed when the loss is still mild and the treatment is most effective when it is initiated before significant downstream damage, i.e. mild cognitive impairment (MCI) or earlier steps. Physiological, neurological analysis, neurological and cognitive tests are clinically diagnosed with AD. A better diagnostic needs to be developed, which is addressed in this paper. We concentrate on Alzheimer's disease in this article and discuss different methods are available to detect Alzheimer's. Reviewed the different data sets available for studying data on Alzheimer's disease and finally comparing appropriate work done in this area.