Towards in-vivo detection of amyloid−β and tau in human CSF using machine learning based Raman spectroscopy

Abstract

This paper aims to present initial proof of concept of a non-invasive early diagnostic tool for Alzheimer disease (AD). The approach is based on the identification using Raman spectroscopy and machine learning algorithms of two proteins that are linked with AD and exist in the cerebrospinal fluid (CSF). As demonstrated in previous studies, the concentration of the proteins amyloid-β and tau may indicate the existence of AD. The proteins’ concentration in the CSF signifies the condition of AD. The current study can contribute to the existing body of knowledge by enabling the development of a non-invasive diagnostic tool that may help with early diagnosis of AD.