Journal of Applied Material Science & Engineering Research(AMSE)

Advanced Technologies for Medicine and Signals ATMS, Department of Electrical and Computer Engineeri, Tunisia

Publications

• Review Article   
  A Comparative Study of PCA and LDA for Dimensionality Reduction in a 4-Way Classification Framework
  Author(s): Besma MABROUK*, Nesrine Jazzar, Ahmed Ben Hamida and Lamia Sellami
  
  Alzheimer's disease (AD), recognized as the second-most impactful neurological disorder and currently incurable, stands as the leading cause of dementia. An imperative research focus is efficiently diagnosing the stages of patients, distinguishing early or late Mild Cognitive Impairment and AD from those with normal cognitive function. Advancements in anatomical and diffusion-weighted imaging, coupled with machine learning techniques, have significantly progressed in this predictive domain. However, in real-world trials, datasets often contain numerous features, and the curse of dimensionality can introduce challenges such as increased computational complexity, overfitting, and diminished model interpretability. To address these issues, the present study explores the efficacy of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) as dimensionality reduction t.. Read More»
  

  Abstract HTML PDF