Journal of clinical monitoring and computing
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J Clin Monit Comput · Jan 2002
Application of artificial neural networks as an indicator of awareness with recall during general anaesthesia.
Awareness with recall is a rare but serious complication of general anaesthesia with an incidence ranging from 0.1%-0.7%. In the absence of a reliable depth-of-anaesthesia monitor, attempts have been made to predict awareness from intraoperative haemodynamic monitoring data, with little success. Artificial neural networks can sometimes detect relationships between input and output variables even when conventional methods fail. Therefore, we subjected standard intraoperative monitoring data to both artificial neural models and conventional statistical methods in an attempt to predict awareness with recall. ⋯ A prediction indicating awareness by the network is very suggestive of true awareness and recall. Blood pressure and heart rate are significantly higher on average in patients with awareness than in patients without. In an individual patient, however, none of our artificial neural models can detect awareness sufficiently reliably.
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J Clin Monit Comput · Jan 2002
The automatic lung parameter estimator (ALPE) system: non-invasive estimation of pulmonary gas exchange parameters in 10-15 minutes.
Clinical measurements of pulmonary gas exchange abnormalities might help prevent hypoxaemia and be useful in monitoring the effects of therapy. In clinical practice single parameters are often used to describe the abnormality e.g., the "effective shunt." A single parameter description is often insufficient, lumping the effects of several abnormalities. A more detailed picture can be obtained from experiments where FiO2 is varied and two parameters estimated. These experiments have previously taken 30-40 minutes to complete, making them inappropriate for routine clinical use. However with automation of data collection and parameter estimation, the experimental time can be reduced to 10-15 minutes. ⋯ The ALPE system provides quick, non-invasive estimation of pulmonary gas exchange parameters and may have several clinical applications. These include, monitoring pulmonary gas exchange abnormalities in the ICU, assessing post-operative gas exchange abnormalities, and titrating diuretic therapy in patients with heart failure.
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Computer simulation models can be extremely valuable for teaching and for understanding real world processes. The discipline of creating a model forces the investigator to carefully define each relationship and test the result. ⋯ Models are typically comprised of systems of differential equations and are solved by numerical integration with computer programs. Spreadsheets, simulation software and custom programs may be used to calculate the numerical solution, draw graphs and animate the result.