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Laser Raman detection of platelets for early and differential diagnosis of Alzheimer’s disease based on an adaptive Gaussian process classification algorithm
- Source :
- Laser Physics. 23:045603
- Publication Year :
- 2013
- Publisher :
- IOP Publishing, 2013.
-
Abstract
- Early and differential diagnosis of Alzheimer's disease (AD) has puzzled many clinicians. In this work, laser Raman spectroscopy (LRS) was developed to diagnose AD from platelet samples from AD transgenic mice and non-transgenic controls of different ages. An adaptive Gaussian process (GP) classification algorithm was used to re-establish the classification models of early AD, advanced AD and the control group with just two features and the capacity for noise reduction. Compared with the previous multilayer perceptron network method, the GP showed much better classification performance with the same feature set. Besides, spectra of platelets isolated from AD and Parkinson's disease (PD) mice were also discriminated. Spectral data from 4 month AD (n = 39) and 12 month AD (n = 104) platelets, as well as control data (n = 135), were collected. Prospective application of the algorithm to the data set resulted in a sensitivity of 80%, a specificity of about 100% and a Matthews correlation coefficient of 0.81. Samples from PD (n = 120) platelets were also collected for differentiation from 12 month AD. The results suggest that platelet LRS detection analysis with the GP appears to be an easier and more accurate method than current ones for early and differential diagnosis of AD.
- Subjects :
- Laser raman
business.industry
Disease
Condensed Matter Physics
Matthews correlation coefficient
Network method
Industrial and Manufacturing Engineering
Atomic and Molecular Physics, and Optics
symbols.namesake
Multilayer perceptron
symbols
Medicine
Platelet
Differential diagnosis
business
Instrumentation
Gaussian process
Algorithm
Subjects
Details
- ISSN :
- 15556611 and 1054660X
- Volume :
- 23
- Database :
- OpenAIRE
- Journal :
- Laser Physics
- Accession number :
- edsair.doi...........6095df2e7a00e5359204dc9312846a47