Diagnosing a pathology with LIBS and biological fluids includes focusing light on to a sample on a substrate to cause ablation of the sample and formation of a plasma, collecting optical emission from the plasma, and providing the optical emission to a spectroscopic acquisition component that provides information on spectral data of the plasma. The spectral data is provided to a machine learning algorithm to diagnose a pathology in the sample, where the algorithm is trained on a training set that includes spectral features in a different spectrum derived from differences between a first LIBS optical emission spectrum collected from one or more sample that have the pathology or known progress of the pathology and a second LIBS optical emission spectrum collected from one or more samples of the predetermined biological fluids that do not have the pathology or the known progress of the pathology.

Diagnosis of disease using laser-induced breakdown spectroscopy and machine learning

Rosalba Gaudiuso;
2022-01-01

Abstract

Diagnosing a pathology with LIBS and biological fluids includes focusing light on to a sample on a substrate to cause ablation of the sample and formation of a plasma, collecting optical emission from the plasma, and providing the optical emission to a spectroscopic acquisition component that provides information on spectral data of the plasma. The spectral data is provided to a machine learning algorithm to diagnose a pathology in the sample, where the algorithm is trained on a training set that includes spectral features in a different spectrum derived from differences between a first LIBS optical emission spectrum collected from one or more sample that have the pathology or known progress of the pathology and a second LIBS optical emission spectrum collected from one or more samples of the predetermined biological fluids that do not have the pathology or the known progress of the pathology.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/472986
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