首页|Linyi University Reports Findings in Machine Learning (Enhancing the accuracy of blood-glucose tests by upgrading FTIR with multiple-reflections, quantum cascad e laser, two-dimensional correlation spectroscopy and machine learning)
Linyi University Reports Findings in Machine Learning (Enhancing the accuracy of blood-glucose tests by upgrading FTIR with multiple-reflections, quantum cascad e laser, two-dimensional correlation spectroscopy and machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting out of Shandong, People’s Rep ublic of China, by NewsRx editors, research stated, “The accuracyof screening d iabetes from non-diabetes is drastically enhanced by strategically upgrading the benchmarkinginfrared spectroscopy technique for non-invasive tests of blood-g lucose, both with state-of-theartinstrumentation-retrofits and with intelligen t spectral-datamining tools. First, the signal-to-noiseperformance of FTIR in m easuring the spectral features of a glucose solution containing bovine serum albumin is improved by 2-3 times with the common single-pass attenuated total-refle ction setup replaced bya multi-passes-reflections setup.”
ShandongPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine Learning
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