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

Rosalba Gaudiuso, Ebo Ewusi-Annan, Weiming Xia, Noureddine Melikechi

Research output: Contribution to journalArticle

1 Scopus citations

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%.

Original languageEnglish (US)
Article number105931
JournalSpectrochimica Acta - Part B Atomic Spectroscopy
Volume171
DOIs
StatePublished - Sep 2020

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Spectroscopy

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