Diagnosis of Alzheimer's disease using laser-induced breakdown spectroscopy and machine learning.

Journal: Spectrochimica acta. Part B, Atomic spectroscopy
Published Date: Jul 15, 2020

Abstract

Alzheimer's disease (AD) is a progressive incurable neurodegenerative disease and a major health problem in aging population. We show that the combined use of Laser-Induced Breakdown Spectroscopy (LIBS) and machine learning applied for the analysis of micro-drops of plasma samples of AD and healthy controls (HC) yields robust classification. Following the acquisition of LIBS spectra of 67 plasma samples from a cohort of 31 AD patients and 36 healthy controls (HC), we successfully diagnose late-onset AD (> 65 years old), with a total classification accuracy of 80%, a specificity of 75% and a sensitivity of 85%.

Authors

  • Rosalba Gaudiuso
    Department of Physics and Applied Physics, Kennedy College of Sciences, University of Massachusetts Lowell, MA 01854, USA.
  • Ebo Ewusi-Annan
    Department of Physics and Applied Physics, Kennedy College of Sciences, University of Massachusetts Lowell, MA 01854, USA.
  • Weiming Xia
    Geriatric Research Education Clinical Center, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA 01730, USA.
  • Noureddine Melikechi
    Department of Physics and Applied Physics, Kennedy College of Sciences, University of Massachusetts Lowell, MA 01854, USA.

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