Introduction: To improve the utilization of continuous- and flash glucose monitoring (CGM/FGM) data we have tested the hypothesis that a machine learning (ML) model can be trained to identify the most likely root causes for hypoglycemic events.
Methods: CGM/FGM data were collected from 449 patients with type 1 diabetes. Of the 42,120 identified hypoglycemic events, 5041 were randomly selected for classification by two clinicians.
The mutual neutralisation of O with O has been studied in a double ion-beam storage ring with combined merged-beams, imaging and timing techniques. Branching ratios were measured at the collision energies of 55, 75 and 170 (± 15) meV, and found to be in good agreement with previous single-pass merged-beams experimental results at 7 meV collision energy. Several previously unidentified spectral features were found to correspond to mutual neutralisation channels of the first metastable state of the cation (O(D), ≈ 3.
View Article and Find Full Text PDF