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Alzheimer’s disease (AD) is a degenerative neurological ailment that causes brain shrinkage and shrinkage of the brain because of death of brain cells. Consequently, it gradually impairs reasoning abilities, memory, and the capacity to complete simple activities. The majority of AD cases are seen in individuals over 65, however it can also strike those in other age groups. Severe brain damage can be avoided if this condition is correctly diagnosed in a timely manner. Many research projects are underway with the goal of early AD detection. Machine learning (ML) and deep learning (DL) techniques are essential to the early treatment of AD in the most recent cutting-edge technology. Convolutional Neural Networks (CNN), a DL model to detect and categorize the images, are the major focus of this work. The result obtained indicates if the individual has AD or not. Additionally, we are by means of the Random Forest and Support Vector Machine classifiers, in this research to compare the outcome with CNN (DL algorithm).

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Assessment of Early-Stage Alzheimer’s Disease Identification by Employing Support Vector Machine and Random Forest Classifier Techniques

  • 会议论文

  • 发表日期：

    2025年

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  • Mahesh V. Sonth,
  • S. V. Suji Aparna,
  • Madhavi Pingili,
  • G. S. Sravanthi,
  • E. N. V. Purna Chandra Rao,
  • S. Krishnaveni

摘要

Alzheimer’s disease (AD) is a degenerative neurological ailment that causes brain shrinkage and shrinkage of the brain because of death of brain cells. Consequently, it gradually impairs reasoning abilities, memory, and the capacity to complete simple activities. The majority of AD cases are seen in individuals over 65, however it can also strike those in other age groups. Severe brain damage can be avoided if this condition is correctly diagnosed in a timely manner. Many research projects are underway with the goal of early AD detection. Machine learning (ML) and deep learning (DL) techniques are essential to the early treatment of AD in the most recent cutting-edge technology. Convolutional Neural Networks (CNN), a DL model to detect and categorize the images, are the major focus of this work. The result obtained indicates if the individual has AD or not. Additionally, we are by means of the Random Forest and Support Vector Machine classifiers, in this research to compare the outcome with CNN (DL algorithm).