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filingDate 2020-02-21^^<http://www.w3.org/2001/XMLSchema#date>
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publicationDate 2020-08-27^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber US-2020268252-A1
titleOfInvention Noninvasive, multispectral-fluorescence characterization of biological tissues with machine/deep learning
abstract Provided is a obtaining an excitation-emission matrix, wherein the excitation-emission matrix is measured with a spectrometer by: illuminating a biological tissue with stimulant light at a first wavelength to cause a first fluorescent emission of light by the biological tissue, measuring a first set of intensities of the first fluorescent emission of light at a plurality of different respective emission wavelengths, illuminating the biological tissue with stimulant light at a second wavelength to cause a second fluorescent emission of light by the biological tissue, and measuring a second set of intensities of the second fluorescent emission of light at a plurality of different respective emission wavelengths; and inferring a classification of the biological tissue or a concentration of a substance in the biological tissue with a multi-layer neural network or other machine learning model.
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