Abstract
Alzheimer’s disease (AD) is one of the most common neurodegenerative
diseases (dementia) among the aged population. In this paper, we propose a unique
machine learning-based framework to discriminate subjects with the first classification
of AD. The training data, preprocessing, feature selection, and classifiers all affect the
output of machine-learning-based methods for AD classification. This chapter
discusses a new comprehensive scheme called Progression Prediction and
Classification of Alzheimer’s Disease using MRI (PPC-AD-MRI). Considering the
data gathered with T1-weighted MRI clinical OASIS progressive information, the
consequences have been evaluated in terms of precision, recall, F1 score, and accuracy.
This recommended model with enhanced accuracy confirms its suitability for use in
AD classification. Other methods can also be used successfully in the disease’s early
detection and diagnosis in medicine and healthcare.
Keywords: Confusion metrics, OASIS dataset, Random Forest Classifier, SGD Gradient Classifier.
Related Journals
Recent Patents on Computer Science
The Chinese Journal of Artificial Intelligence
Current Chinese Computer Science
Journal of Fuzzy Logic and Modeling in Engineering
Recent Advances in Computer Science and Communications
International Journal of Sensors, Wireless Communications and Control
Journal of Intelligent Systems in Current Computer Engineering
Current E-Learning
Current Computer Science
Wireless and Communication Letters
Related Books
Computational Intelligence For Data Analysis
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
A First Course in Artificial Intelligence
Artificial Intelligence: Models, Algorithms and Applications
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
Handbook of Mobile Application Development: A Guide to Selecting the Right Engineering and Quality Features
Applications of Modern High Performance Networks
Arduino Meets Matlab: Interfacing, Programs and Simulink
Arduino and SCILAB based Projects
Application of Chaos and Fractals to Computer Vision