Machine learning based analysis and detection of trend outliers for electromyographic neuromuscular monitoring

ConclusionsEngineered TOF-R trend features and the resulting Cost-Sensitive Logistic Regression (CSLR) models provide useful insights and serve as a potential first step towards the automated removal of outliers for neuromuscular monitoring devices.Trial registrationNCT04518761 (clinicaltrials.gov), registered on 19 August 2020.
Source: Journal of Clinical Monitoring and Computing - Category: Information Technology Source Type: research