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A Framework for Early Recognition of Alzheimer’s Using Machine Learning Approaches

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Intelligent System Design

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 494))

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Abstract

Alzheimer’s disease is a neurological disorder of the brain that primarily affects the blood nuclear cells in our brain. Early detection of Alzheimer’s disease is extremely crucial for disease prevention. Recently, the developers proposed a pre-selection technique for measuring image similarity. However, this method has a high computation time and a lengthy process. As a result, propose a novel machine learning framework for classifying Alzheimer’s disease. In this paper, several machine learning algorithms are used to classify Alzheimer’s disease in order to predict it at an early stage. Some of these include random forest, SVM, decision tree, and XGB classifier. Based on these algorithms propose a CatBoost classifier for the highest accuracy. These algorithms are applied on the OASIS dataset. In these algorithms, the CatBoost classifier achieves 85.7% accuracy on the OASIS dataset. The findings show that this framework can be used to identify and treat Alzheimer’s disease in healthcare at an early stage.

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Author information

Authors and Affiliations

  1. MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India

    Lolla Kiran Kumar

  2. Department of Computer Science & Engineering, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India

    P. Srinivasa Rao & S. Sreenivasa Rao

Authors
  1. Lolla Kiran Kumar
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  2. P. Srinivasa Rao
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  3. S. Sreenivasa Rao
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Corresponding author

Correspondence to Lolla Kiran Kumar .

Editor information

Editors and Affiliations

  1. Dr. A.P.J. Abdul Kalam Technical University, Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. Principal, BVRIT Hyd. College of Engineering for Women, Hyderabad, Telangana, India

    K. V. N. Sunitha

  3. College of Information Science and Eng, Ritsumeikan University, Kusuatsu, Shiga, Japan

    Yen-Wei Chen

  4. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kumar, L.K., Srinivasa Rao, P., Sreenivasa Rao, S. (2023). A Framework for Early Recognition of Alzheimer’s Using Machine Learning Approaches. In: Bhateja, V., Sunitha, K.V.N., Chen, YW., Zhang, YD. (eds) Intelligent System Design. Lecture Notes in Networks and Systems, vol 494. Springer, Singapore. https://doi.org/10.1007/978-981-19-4863-3_1

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