Research Area:  Machine Learning

Abstract:

The Alzheimers disease accurate early-stage detection is critically necessary for effective treatment and recovery. Therefore, accurate detection of Alzheimers disease is a great research problem. Different researchers used various techniques to detect Alzheimers disease effectively however; these methods still have lack of prediction accuracy. In this study we proposed machine learning-based method to diagnosis Alzheimers disease accurately. We used machine learning classifiers for accurate prediction of Alzheimers disease. Alzheimers Disease Neuroimaging Initiative data set has been used to check the proposed method performance. The experimental results demonstrate that logistic regression performance was excellent in terms of accuracy and achieved optimal accuracy 98.12%.Thus, it is recommended for effective early detection of Alzheimers Disease.

Keywords:  
Dementia
Logistics
Support vector machines
Machine learning
Mathematical model
Sensitivity

Author(s) Name:  Muhammad Hammad Memon; Jianping Li; Amin Ul Haq;

Publisher name:  IEEE

DOI:  10.1109/ICCWAMTIP47768.2019.9067689

Volume Information:  

Paper Link:   https://ieeexplore.ieee.org/abstract/document/9067689/