{"title":"The Early Confirmation of Alzheimer’s Disease using Internet Sources","authors":"C. Sandeep, A. Sukesh Kumar","doi":"10.51983/ajsat-2017.6.1.943","DOIUrl":null,"url":null,"abstract":"Alzheimer Disease (AD) is one of the common forms of dementia which is an irreversible neurodegenerative progressive disorder of the brain which affects the elderly population above the age of 65. Alzheimer is a brain disease that causes problems with memory, thinking and behaviour. It is severe enough to interfere with daily activities. Alzheimer symptoms are characterized by memory loss that affects day-to-day function, difficulty performing familiar tasks, problems with language, disorientation of time and place, poor or decreased judgment, problems with abstract thinking, misplacing things, changes in mood and behaviour, changes in personality and loss of initiative. There are different types of tests associated with AD such as neuropsychological tests, laboratory tests and various imaging modalities for the early diagnosis of AD. Although these tests are available, they are inadequate for the definite diagnosis of the disease. In this paper we focus on the databases related to AD such as ADNI (Alzheimer’s Disease Neuroimaging Initiative), TREAD (Trajectory-Related Early Alzheimer’s Database), CAMD (Coalition Against Major Diseases), and NAAC( National Alzheimer’s Coordinating Center). The use of these internet sources, soft computing techniques and image analysis from the different imaging modalities in an efficient way for making a definite diagnosis and early confirmation of AD. Our aim is to predict the early diagnosis in a reliable manner such that to combine the values of different tests with the help of soft computing techniques to develop software tool for a definite diagnosis.","PeriodicalId":414891,"journal":{"name":"Asian Journal of Science and Applied Technology","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Science and Applied Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51983/ajsat-2017.6.1.943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Alzheimer Disease (AD) is one of the common forms of dementia which is an irreversible neurodegenerative progressive disorder of the brain which affects the elderly population above the age of 65. Alzheimer is a brain disease that causes problems with memory, thinking and behaviour. It is severe enough to interfere with daily activities. Alzheimer symptoms are characterized by memory loss that affects day-to-day function, difficulty performing familiar tasks, problems with language, disorientation of time and place, poor or decreased judgment, problems with abstract thinking, misplacing things, changes in mood and behaviour, changes in personality and loss of initiative. There are different types of tests associated with AD such as neuropsychological tests, laboratory tests and various imaging modalities for the early diagnosis of AD. Although these tests are available, they are inadequate for the definite diagnosis of the disease. In this paper we focus on the databases related to AD such as ADNI (Alzheimer’s Disease Neuroimaging Initiative), TREAD (Trajectory-Related Early Alzheimer’s Database), CAMD (Coalition Against Major Diseases), and NAAC( National Alzheimer’s Coordinating Center). The use of these internet sources, soft computing techniques and image analysis from the different imaging modalities in an efficient way for making a definite diagnosis and early confirmation of AD. Our aim is to predict the early diagnosis in a reliable manner such that to combine the values of different tests with the help of soft computing techniques to develop software tool for a definite diagnosis.