17th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics

CIBB 2021

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Technical Session

CIBB 2021 - Neurodegenrative Diseases Session

Computer-aided diagnosis system for Alzheimer’s disease using principal component analysis and machine learning-based approaches

  Lilia Lazli


Alzheimer’s Disease is a severe neurological brain disorder. It is not curable, but earlier detection can help improve symptoms in a great deal. The machine learning-based approaches are popular and well-motivated models for many medical image processing tasks such as computer-aided diagnosis. These techniques can vastly improve the process for accurate diagnosis of Alzheimer’s Disease. In this paper, we investigate the performance of these techniques for Alzheimer’s Disease detection and classification using brain MRI and PET images from the OASIS database. The proposed system takes advantage of the powerful artificial neural network and support vector machines as classifiers. As well as principal component analysis as a feature extraction technique. The results indicate that the combined scheme achieves good accuracy and offers a significant advantage over the other approaches.


Lilia Lazli
  ÉTS – University of Quebec, Canada


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