Prediction of human triglyceride concentration based on quantum genetic-partial least squares algorithm and fluorescence spectroscopy.

It is an important subject with practical significance in modern medical testing about how to obtain various indicators in blood effectively and conveniently. In this essay, the prediction model of triglyceride (TG) concentration was studied based on the fluorescence spectrum of human serum. Firstly, the concept of effective signal intensity was proposed based on the results of wavelet decomposition that the noise signals of spectrum was mainly distributed in the first and second detailed components, and 280 nm was selected as the optimal excitation wavelength for modeling.