Raman hyperspectroscopy of saliva and machine learning for sjögren’s disease diagnostics

HIGHLIGHTS

• Who: Bhavik Vyas from the Department University at have published the paper: Raman hyperspectroscopy of saliva and machine learning for Sjögren’s disease diagnostics, in the Journal: Scientific Reports Scientific Reports

SUMMARY

Supervised multivariate analysis, including machine_learning algorithms, can identify these multiple small but specific differences between spectral signatures and build diagnostic classification models based on them. The PLS toolbox offers an outliers removal technique for the PLS_DA model called T ­ 2 ­Hotelling29. With the help of GA, SVM_DA selects the area (data points) of the spectra specific to each class and . . .

 



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