首页|Russian Academy of Sciences Reports Findings in Machine Learning (Machine learning assisted rapid approach for quantitative prediction of biochemical parameters of blood serum with FTIR spectroscopy)
Russian Academy of Sciences Reports Findings in Machine Learning (Machine learning assisted rapid approach for quantitative prediction of biochemical parameters of blood serum with FTIR spectroscopy)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting originating from Troitsk, Rus sia, by NewsRx correspondents, research stated, “This study develops regression models for predicting blood biochemical data using Fourier-transform infrared sp ectroscopy (FTIR) analysis. Absorption at specific wavelengths of blood serum is revealed to have strong correlations with biochemical parameters, such as ALT, amylase, AST, protein, bilirubin, Gamma-GT, iron, calcium, uric acid, triglyceri des, phosphatase and cholesterol, were shown.”
TroitskRussiaEurasiaAmylasesBiochemicalsBiochemistryChemicalsCyborgsEmerging TechnologiesEnzymes and CoenzymesMachine Learning
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