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This paper aims to establish a patient's intracranial pressure (ICP) model in neurosurgical intensive care unit (NICU) using neural network.
Finally, we used this SRNNTT model to build the ICP model using data from six head-injured patients.
We demonstrate the consistency, accuracy, and efficiency of the upscaling workflow using a realistic pattern-scale ICP model.
Although the accuracy of the ICP model is still far from ideal, the methodology used non-invasive vital signs (i.e., MAP, HR, EtCO2, and rSO2) to predict an invasive, dangerous and expensive signal (i.e., ICP) has achieved this monitoring system more safely and flexibly in NICU.
Preserved aqueous samples were analyzed for metal cation concentrations using a Varian ICP Model 720-ES ICP-OES utilizing EPA Method 6010B.
Acidified aqueous samples were analyzed for metal cation concentrations using a Varian ICP Model 720-ES ICP-OES utilizing EPA Method 6010B.
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Table 2 LA-ICP-MS operating conditions ICP-MS Model Thermo Elemental X series 2 Incident power 1200 W Gas flows Plasma 13 L min−1 Auxiliary 0.80 L min−1 Carrier 0.70 L min−1 Cones Platinum Dwell time 30 ms ThO+/Th+ <1 % Laser ablation Model New wave UP-213 Laser UV Nd YAG 213 nm Pulse energy 0.54 mJ Repetition rate 10 Hz.
ICP-OES measurements were acquired by use of a Perkin Elmer ICP-OES model Optima 4100 DV, USA.
Inductively coupled plasma-optical emission spectrometry (ICP-OES) measurements were acquired by use of a Perkin Elmer ICP-OES model Optima 4100 DV (Waltham, MA, USA).
ICP-OES measurements were acquired with the use of a Perkin Elmer ICP-OES model Optima 4100 DV, Shelton, CT, USA.
Elemental analysis was performed by inductivity coupled plasma on Varian, Australia, ICP-OES, model Vista Pro spectrometry.
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