His main research concerns Electroencephalography, Anesthesia, Neuroscience, Artificial intelligence and Propofol. His Clinical neurophysiology study, which is part of a larger body of work in Electroencephalography, is frequently linked to In patient, bridging the gap between disciplines. His Anesthesia study incorporates themes from Alpha and Coherence analysis.
Many of his research projects under Neuroscience are closely connected to Cortical spreading depression with Cortical spreading depression, tying the diverse disciplines of science together. The study incorporates disciplines such as Machine learning and Polysomnography in addition to Artificial intelligence. His Propofol research includes themes of Sevoflurane, Anesthetic, Coherence and Alpha rhythm.
M. Brandon Westover spends much of his time researching Electroencephalography, Artificial intelligence, Anesthesia, Internal medicine and Epilepsy. His Electroencephalography study combines topics from a wide range of disciplines, such as Status epilepticus and Audiology. His research integrates issues of Machine learning and Pattern recognition in his study of Artificial intelligence.
His study in Anesthesia focuses on Propofol, Subarachnoid hemorrhage, Sedation and Anesthetic. His Epilepsy study is associated with Neuroscience. His research investigates the connection between Burst suppression and topics such as Coma that intersect with issues in Intensive care medicine.
M. Brandon Westover mainly investigates Electroencephalography, Artificial intelligence, Internal medicine, Pattern recognition and Epilepsy. M. Brandon Westover works on Electroencephalography which deals in particular with Ictal. He combines subjects such as Machine learning, Receiver operating characteristic and Natural language processing with his study of Artificial intelligence.
As a part of the same scientific study, M. Brandon Westover usually deals with the Internal medicine, concentrating on Cardiology and frequently concerns with Neurology, Subarachnoid hemorrhage, Severity of illness and Public health. His studies deal with areas such as Artificial neural network, Respiratory system and False positive rate as well as Pattern recognition. The subject of his Epilepsy research is within the realm of Neuroscience.
The scientist’s investigation covers issues in Electroencephalography, Internal medicine, Retrospective cohort study, Cohort and Artificial intelligence. Specifically, his work in Electroencephalography is concerned with the study of Ictal. His Internal medicine study integrates concerns from other disciplines, such as Delirium and Cardiology.
His studies in Retrospective cohort study integrate themes in fields like Disseminated intravascular coagulation, Respiratory failure, Coma and Autopsy. His biological study deals with issues like Cohort study, which deal with fields such as Tracheal intubation, Intensive care, Mechanical ventilation, Algorithm and Relative risk. His study in Adverse effect is interdisciplinary in nature, drawing from both Anesthesia and Burst suppression.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Exact Discovery of Time Series Motifs.
Abdullah Mueen;Eamonn J. Keogh;Qiang Zhu;Sydney Cash.
siam international conference on data mining (2009)
The continuum of spreading depolarizations in acute cortical lesion development: Examining Leão's legacy
Jed A Hartings;C William Shuttleworth;Sergei A Kirov;Cenk Ayata.
Journal of Cerebral Blood Flow and Metabolism (2017)
Recording, analysis, and interpretation of spreading depolarizations in neurointensive care: Review and recommendations of the COSBID research group
Jens P. Dreier;Martin Fabricius;Cenk Ayata;Oliver W. Sakowitz.
Journal of Cerebral Blood Flow and Metabolism (2017)
Sparse Extreme Learning Machine for Classification
Zuo Bai;Guang-Bin Huang;Danwei Wang;Han Wang.
IEEE Transactions on Systems, Man, and Cybernetics (2014)
Effects of sevoflurane and propofol on frontal electroencephalogram power and coherence.
Oluwaseun Akeju;M. Brandon Westover;M. Brandon Westover;Kara J. Pavone;Aaron L. Sampson.
Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling.
Nishant Sinha;Justin Dauwels;Marcus Kaiser;Sydney S. Cash.
Exploration and Modulation of Brain Network Interactions with Noninvasive Brain Stimulation in Combination with Neuroimaging
Mouhsin M. Shafi;M. Brandon Westover;M. Brandon Westover;Michael D. Fox;Michael D. Fox;Alvaro Pascual-Leone;Alvaro Pascual-Leone;Alvaro Pascual-Leone.
European Journal of Neuroscience (2012)
Interrater agreement for Critical Care EEG Terminology.
Nicolas Gaspard;Lawrence J. Hirsch;Suzette M. LaRoche;Cecil D. Hahn.
Statin use following intracerebral hemorrhage: a decision analysis.
M. Brandon Westover;Matt T. Bianchi;Mark H. Eckman;Steven M. Greenberg.
JAMA Neurology (2011)
Expert-level sleep scoring with deep neural networks.
Siddharth Biswal;Haoqi Sun;Balaji Goparaju;M Brandon Westover.
Journal of the American Medical Informatics Association (2018)
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