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dc.contributor.author
Weiss, Shennan A.
dc.contributor.author
Waldman, Zachary
dc.contributor.author
Raimondo, Federico
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Fernandez Slezak, Diego
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Donmez, Mustafa
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Worrell, Gregory
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Bragin, Anatol
dc.contributor.author
Engel, Jerome
dc.contributor.author
Staba, Richard
dc.contributor.author
Sperling, Michael
dc.date.available
2020-12-23T16:52:13Z
dc.date.issued
2019-04
dc.identifier.citation
Weiss, Shennan A.; Waldman, Zachary; Raimondo, Federico; Fernandez Slezak, Diego; Donmez, Mustafa; et al.; Localizing epileptogenic regions using high-frequency oscillations and machine learning; Future Medicine; Biomarkers In Medicine; 13; 5; 4-2019; 409-418
dc.identifier.issn
1752-0363
dc.identifier.uri
http://hdl.handle.net/11336/121142
dc.description.abstract
Pathological high frequency oscillations (HFOs) are putative neurophysiological biomarkers of epileptogenic brain tissue. Utilizing HFOs for epilepsy surgery planning offers the promise of improved seizure outcomes for patients with medically refractory epilepsy. This review discusses possible machine learning strategies that can be applied to HFO biomarkers to better identify epileptogenic regions. We discuss the role of HFO rate, and utilizing features such as explicit HFO properties (spectral content, duration, and power) and phase-amplitude coupling for distinguishing pathological HFO (pHFO) events from physiological HFO events. In addition, the review highlights the importance of neuroanatomical localization in machine learning strategies.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Future Medicine
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ARTIFICIAL INTELLIGENCE
dc.subject
EPILEPSY
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EPILEPSY SURGERY
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EPILEPTIFORM SPIKE
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FAST RIPPLE
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HFO
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HIGH-FREQUENCY OSCILLATION
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MACHINE LEARNING
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PHASE-AMPLITUDE COUPLING
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RIPPLE
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SEIZURE
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WAVELET
dc.subject.classification
Ciencias de la Computación
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Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Localizing epileptogenic regions using high-frequency oscillations and machine learning
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-11-30T14:16:06Z
dc.journal.volume
13
dc.journal.number
5
dc.journal.pagination
409-418
dc.journal.pais
Reino Unido
dc.journal.ciudad
Londres
dc.description.fil
Fil: Weiss, Shennan A.. Thomas Jefferson University; Estados Unidos
dc.description.fil
Fil: Waldman, Zachary. Thomas Jefferson University; Estados Unidos
dc.description.fil
Fil: Raimondo, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
dc.description.fil
Fil: Fernandez Slezak, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
dc.description.fil
Fil: Donmez, Mustafa. Thomas Jefferson University; Estados Unidos
dc.description.fil
Fil: Worrell, Gregory. Mayo Systems Electrophysiology Laboratory; Estados Unidos
dc.description.fil
Fil: Bragin, Anatol. David Geffen School of Medicine at UCLA; Estados Unidos
dc.description.fil
Fil: Engel, Jerome. David Geffen School of Medicine at UCLA; Estados Unidos
dc.description.fil
Fil: Staba, Richard. David Geffen School of Medicine at UCLA; Estados Unidos
dc.description.fil
Fil: Sperling, Michael. Thomas Jefferson University; Estados Unidos
dc.journal.title
Biomarkers In Medicine
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.futuremedicine.com/doi/10.2217/bmm-2018-0335
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.2217/bmm-2018-0335
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