Diagnosis of Alzheimer's disease using Naive Bayesian Classifier

• Published in: Neural computing & applications Vol. 29; no. 1; pp. 123 - 132
• Main Authors: Bhagya Shree, S. R., Sheshadri, H. S.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.01.2018; Springer Nature B.V
• Subjects: Alzheimer's disease; Artificial Intelligence; Bayesian analysis; Brain; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Dementia; Diagnosis; Image Processing and Computer Vision; Original Article; Probability and Statistics in Computer Science; Salmon; 10/66 Battery; Feature selection; Naive Bayes; Alzheimer's disease; Dementia
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-016-2416-3

In the world of modern medicine, though there is lot of medical achievements, some diseases still continue to pest the human race. Unfortunately, dementia is one such disease. All over the world, a large number of people are suffering from dementia. Dementia is a brain-related disease. Diagnosis of the disease at the earlier stage is the requirement of the day. Alzheimer's disease (AD) is one of the types of the dementia, and around 60 % of demented are affected from Alzheimer’s disease (Salmon and Bondi in Neuro psychological assessment of dementia. National Institutes of Health, 2010 ). All over the world, there are around 35 million people suffering from AD and this number is expected to double by 2030 and more than triple by 2050, that is to 115 million (Prince et al. in World Alzheimer report 2013: journey of caringan analysis of long-term care for dementia. Kings College, London, 2013 ). Diagnosis of this disease at an early stage will help the patients to lead a quality life for the remaining tenure of their life. In this paper, the authors have collected data of 466 subjects by conducting neuropsychological tests. The authors focus on diagnosis of AD for neuropsychological tests using Naive Bayes.