Cargando…

Exploratory Outlier Detection for Acceleromyographic Neuromuscular Monitoring: Machine Learning Approach

BACKGROUND: Perioperative quantitative monitoring of neuromuscular function in patients receiving neuromuscular blockers has become internationally recognized as an absolute and core necessity in modern anesthesia care. Because of their kinetic nature, artifactual recordings of acceleromyography-bas...

Descripción completa

Detalles Bibliográficos
Autores principales:	Verdonck, Michaël, Carvalho, Hugo, Berghmans, Johan, Forget, Patrice, Poelaert, Jan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2021
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8768027/ https://www.ncbi.nlm.nih.gov/pubmed/34152273 http://dx.doi.org/10.2196/25913

Ejemplares similares

Comparison of onset of neuromuscular blockade with electromyographic and acceleromyographic monitoring: a prospective clinical trial
por: Chaves-Cardona, Harold E., et al.
Publicado: (2023)

Monitoring of neuromuscular blockade by pulse oximetry tracing: A simple modification of mechanomyographic and acceleromyographic principles
por: Das, Jyotirmoy, et al.
Publicado: (2011)

Acceptance of mHealth among health professionals: a case study on anesthesia practitioners
por: Carvalho, Hugo, et al.
Publicado: (2020)

A comparison of a prototype electromyograph vs. a mechanomyograph and an acceleromyograph for assessment of neuromuscular blockade
por: Bowdle, A., et al.
Publicado: (2019)

Correction to: Mindray 3-directional NMT Module (a new generation “Tri-axial” neuromuscular monitor) versus the Relaxometer mechanomyograph and versus the TOF-Watch SX acceleromyograph
por: Dahaba, Ashraf A., et al.
Publicado: (2019)

Machine Learning Based Outlier Detectionfor Data Certification
por: Payoungkhamdee, Patomporn
Publicado: (2019)

Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots
por: Yang, Song, et al.
Publicado: (2007)

Outlier Detection with Reinforcement Learning for Costly to Verify Data
por: Nijhuis, Michiel, et al.
Publicado: (2023)

Paired evaluation of machine-learning models characterizes effects of confounders and outliers
por: Nariya, Maulik K., et al.
Publicado: (2023)

Paired evaluation of machine-learning models characterizes effects of confounders and outliers
por: Nariya, Maulik K., et al.
Publicado: (2023)

Outlier detection using autoencoders
por: Lyudchik, Olga
Publicado: (2016)

Subgroup and outlier detection analysis
por: Wu, Gang, et al.
Publicado: (2013)

Outlier detection in BLAST hits
por: Shah, Nidhi, et al.
Publicado: (2018)

Fluctuation-based outlier detection
por: Du, Xusheng, et al.
Publicado: (2023)

Perceptual learning of ensemble and outlier perception
por: Hochstein, Shaul, et al.
Publicado: (2020)

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers
por: Maniruzzaman, Md., et al.
Publicado: (2018)

Classification of red blood cell shapes in flow using outlier tolerant machine learning
por: Kihm, Alexander, et al.
Publicado: (2018)

Distribution of Variables by Method of Outlier Detection
por: Finch, W. Holmes
Publicado: (2012)

Qualitative Data Clustering to Detect Outliers
por: Nowak-Brzezińska, Agnieszka, et al.
Publicado: (2021)

Prediction and outlier detection in classification problems
por: Guan, Leying, et al.
Publicado: (2022)

Analytical method for detecting outlier evaluators
por: Wu, Yujie, et al.
Publicado: (2023)

Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine
por: Mourão-Miranda, Janaina, et al.
Publicado: (2011)

Detection of outlier loci and their utility for fisheries management
por: Russello, Michael A, et al.
Publicado: (2012)

Outlier detection: a data mining perspective
por: Ranga Suri, N N R, et al.
Publicado: (2019)

MOF: An R Function to Detect Outlier Microarray
por: Yang, Song, et al.
Publicado: (2008)

Identification of outliers
por: Hawkins, D M
Publicado: (1980)

Outlier analysis
por: Aggarwal, Charu C
Publicado: (2013)

Assessment of the New Acceleromyograph TOF 3D Compared with the Established TOF Watch SX: Bland-Altman Analysis of the Precision and Limits of Agreement between Both Devices—A Randomized Clinical Comparison
por: Soltesz, Stefan, et al.
Publicado: (2022)

Variation in Caesarean Section Rates in the US: Outliers, Damned Outliers, and Statistics
por: Smith, Gordon C. S.
Publicado: (2014)

Application of microarray outlier detection methodology to psychiatric research
por: Ernst, Carl, et al.
Publicado: (2008)

LSOSS: Detection of Cancer Outlier Differential Gene Expression
por: Wang, Yupeng, et al.
Publicado: (2010)

Evaluation of Different Outlier Detection Methods for GPS Networks
por: Gökalp, Ertan, et al.
Publicado: (2008)

Query-Based Outlier Detection in Heterogeneous Information Networks
por: Kuck, Jonathan, et al.
Publicado: (2015)

Procedure for Detecting Outliers in a Circular Regression Model
por: Rambli, Adzhar, et al.
Publicado: (2016)

OD-seq: outlier detection in multiple sequence alignments
por: Jehl, Peter, et al.
Publicado: (2015)

Stratification-Based Outlier Detection over the Deep Web
por: Xian, Xuefeng, et al.
Publicado: (2016)

Outlier Detection in Urban Air Quality Sensor Networks
por: van Zoest, V. M., et al.
Publicado: (2018)

Identification of differentially expressed genes by means of outlier detection
por: Irigoien, Itziar, et al.
Publicado: (2018)

A note on detecting statistical outliers in psychophysical data
por: Jones, Pete R.
Publicado: (2019)

Convolutional Neural Network-Based Discriminator for Outlier Detection
por: Alharbi, Fahad, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_juftt1pvsrrbeoiutaihblt48l