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

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.