GENETIC ALGORITHM-BASED DECISION TREE OPTIMIZATION FOR DETECTION OF DEMENTIA THROUGH MRI ANALYSIS

Govada Anuradha; Harini Davu; Muthyalanaidu Karri

doi:10.35784/iapgos.5775

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Published: Mar 31, 2024

DOI: https://doi.org/10.35784/iapgos.5775

Issue Vol. 14 No. 1 (2024)

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DOI

https://doi.org/10.35784/iapgos.5775

Authors

Govada Anuradha

ganuradha@vrsiddhartha.ac.in

Velagapudi Ramakrishna Siddhartha Engineering College, Department of Computer Science and Engineering, India

https://orcid.org/0000-0002-0999-0376

Harini Davu

davuharini@gmail.com

Velagapudi Ramakrishna Siddhartha Engineering College, Department of Computer Science and Engineering, India

https://orcid.org/0009-0008-6187-1797

Muthyalanaidu Karri

karrimuthyalanaidu3802@gmail.com

Velagapudi Ramakrishna Siddhartha Engineering College, Department of Computer Science and Engineering, India

https://orcid.org/0009-0006-5850-3761

Abstract

Dementia is a devastating neurological disorder that affects millions of people globally, causing progressive decline in cognitive function and daily living activities. Early and precise detection of dementia is critical for optimal dementia therapy and management however, the diagnosis of dementia is often challenging due to the complexity of the disease and the wide range of symptoms that patients may exhibit. Machine learning approaches are becoming progressively more prevalent in the realm of image processing, particularly for disease prediction. These algorithms can learn to recognize distinctive characteristics and patterns that are suggestive of specific diseases by analyzing images from multiple medical imaging modalities. This paper aims to develop and optimize a decision tree algorithm for dementia detection using the OASIS dataset, which comprises a large collection of MRI images and associated clinical data. This approach involves using a genetic algorithm to optimize the decision tree model for maximum accuracy and effectiveness. The ultimate goal of the paper is to develop an effective, non-invasive diagnostic tool for early and accurate detection of dementia. The GA-based decision tree, as proposed, exhibits strong performance compared to alternative models, boasting an impressive accuracy rate of 96.67% according to experimental results.

Keywords:

dementia, genetic algorithm, decision tree

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Anuradha, G., Davu, H., & Karri, M. (2024). GENETIC ALGORITHM-BASED DECISION TREE OPTIMIZATION FOR DETECTION OF DEMENTIA THROUGH MRI ANALYSIS. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 14(1), 83–89. https://doi.org/10.35784/iapgos.5775

GENETIC ALGORITHM-BASED DECISION TREE OPTIMIZATION FOR DETECTION OF DEMENTIA THROUGH MRI ANALYSIS

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