Early Diagnosis of Alzheimer's Disease using Machine Learning Techniques - A Review Paper

Aunsia Khan, Muhammad Usman

Abstract

Alzheimer’s, an irreparable brain disease, impairs thinking and memory while the aggregate mind size shrinks which at last prompts demise. Early diagnosis of AD is essential for the progress of more prevailing treatments. Machine learning (ML), a branch of artificial intelligence, employs a variety of probabilistic and optimization techniques that permits PCs to gain from vast and complex datasets. As a result, researchers focus on using machine learning frequently for diagnosis of early stages of AD. This paper presents a review, analysis and critical evaluation of the recent work done for the early detection of AD using ML techniques. Several methods achieved promising prediction accuracies, however they were evaluated on different pathologically unproven data sets from different imaging modalities making it difficult to make a fair comparison among them. Moreover, many other factors such as pre-processing, the number of important attributes for feature selection, class imbalance distinctively affect the assessment of the prediction accuracy. To overcome these limitations, a model is proposed which comprise of initial pre-processing step followed by imperative attributes selection and classification is achieved using association rule mining. Furthermore, this proposed model based approach gives the right direction for research in early diagnosis of AD and has the potential to distinguish AD from healthy controls.

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Paper Citation


in Harvard Style

Khan A. and Usman M. (2015). Early Diagnosis of Alzheimer's Disease using Machine Learning Techniques - A Review Paper . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 380-387. DOI: 10.5220/0005615203800387


in Bibtex Style

@conference{kdir15,
author={Aunsia Khan and Muhammad Usman},
title={Early Diagnosis of Alzheimer's Disease using Machine Learning Techniques - A Review Paper},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={380-387},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005615203800387},
isbn={978-989-758-158-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - Early Diagnosis of Alzheimer's Disease using Machine Learning Techniques - A Review Paper
SN - 978-989-758-158-8
AU - Khan A.
AU - Usman M.
PY - 2015
SP - 380
EP - 387
DO - 10.5220/0005615203800387