Classification algorithms for the identification of structural injury in TBI using brain electrical activity.
Background: There is an urgent need for objective criteria adjunctive to standard clinical assessment of acute Traumatic Brain Injury (TBI). Details of the development of a quantitative index to identify structural brain injury based on brain electrical activity will be described.Methods: Acute clos...
| Publicado en: | Computers in Biology & Medicine Vol. 53; pp. 125 - 134 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Oct2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109762057&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109762057 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00104825 JC2 jtl: Computers in Biology & Medicine issn: 00104825 maglogo: N pubinfo: dt: Oct2014 vid: 53 pid: 82545 pub: Elsevier B.V. place: Philadelphia, Pennsylvania artinfo: ui: 109762057 109947609 NLM25137412 2012785153 10.1016/j.compbiomed.2014.07.011 NLM25137412 109762057 ppf: 125 ppct: 9 formats: tig: atl: Classification algorithms for the identification of structural injury in TBI using brain electrical activity. aug: au: Prichep, Leslie S Ghosh Dastidar, Samanwoy Jacquin, Arnaud Koppes, William Miller, Jonathan Radman, Thomas O'Neil, Brian Naunheim, Rosanne Huff, J Stephen affil: Brain Research Laboratories, Department of Psychiatry, NYU School of Medicine, New York, NY, USA. Electronic address: Leslie.Prichep@nyumc.org. sug: subj: Classification Algorithms Brain Injuries Pathology Brain Injuries Physiopathology Diagnosis, Computer Assisted Methods Electroencephalography Methods Adolescence Adult Aged Aged, 80 and Over Brain Pathology Brain Physiopathology Female Human Male Middle Age Models, Statistical Tomography, X-Ray Computed Young Adult Adolescent: 13-18 years Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Background: There is an urgent need for objective criteria adjunctive to standard clinical assessment of acute Traumatic Brain Injury (TBI). Details of the development of a quantitative index to identify structural brain injury based on brain electrical activity will be described.Methods: Acute closed head injured and normal patients (n=1470) were recruited from 16 US Emergency Departments and evaluated using brain electrical activity (EEG) recorded from forehead electrodes. Patients had high GCS (median=15), and most presented with low suspicion of brain injury. Patients were divided into a CT positive (CT+) group and a group with CT negative findings or where CT scans were not ordered according to standard assessment (CT-/CT_NR). Three different classifier methodologies, Ensemble Harmony, Least Absolute Shrinkage and Selection Operator (LASSO), and Genetic Algorithm (GA), were utilized.Results: Similar performance accuracy was obtained for all three methodologies with an average sensitivity/specificity of 97.5%/59.5%, area under the curves (AUC) of 0.90 and average Negative Predictive Validity (NPV)>99%. Sensitivity was highest for CT+ cases with potentially life threatening hematomas, where two of three classifiers were 100%.Conclusion: Similar performance of these classifiers suggests that the optimal separation of the populations was obtained given the overlap of the underlying distributions of features of brain activity. High sensitivity to CT+ injuries (highest in hematomas) and specificity significantly higher than that obtained using ED guidelines for imaging, supports the enhanced clinical utility of this technology and suggests the potential role in the objective, rapid and more optimal triage of TBI patients. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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