Assessment of a simple artificial neural network for predicting residual neuromuscular block
Postoperative residual curarization (PORC) after surgery is common and its detection has a high error rate. Artificial neural networks are being used increasingly to examine complex data. We hypothesized that a neural network would enhance prediction of PORC. In 40 previously reported patients, neur...
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Veröffentlicht in: | British journal of anaesthesia : BJA 2003-01, Vol.90 (1), p.48-52 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Postoperative residual curarization (PORC) after surgery is common and its detection has a high error rate. Artificial neural networks are being used increasingly to examine complex data. We hypothesized that a neural network would enhance prediction of PORC.
In 40 previously reported patients, neuromuscular function, neuromuscular block/antagonist usage and time intervals were recorded throughout anaesthesia until tracheal extubation by an observer uninvolved in patient care. PORC was defined as significant ‘fade’ (train of four |
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ISSN: | 0007-0912 1471-6771 |
DOI: | 10.1093/bja/aeg015 |