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A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers
OBJECTIVE: To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data. METHOD: Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert E...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5476904/ https://www.ncbi.nlm.nih.gov/pubmed/28531810 http://dx.doi.org/10.1016/j.clinph.2017.04.016 |
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author | Sharma, Niraj K. Pedreira, Carlos Centeno, Maria Chaudhary, Umair J. Wehner, Tim França, Lucas G.S. Yadee, Tinonkorn Murta, Teresa Leite, Marco Vos, Sjoerd B. Ourselin, Sebastien Diehl, Beate Lemieux, Louis |
author_facet | Sharma, Niraj K. Pedreira, Carlos Centeno, Maria Chaudhary, Umair J. Wehner, Tim França, Lucas G.S. Yadee, Tinonkorn Murta, Teresa Leite, Marco Vos, Sjoerd B. Ourselin, Sebastien Diehl, Beate Lemieux, Louis |
author_sort | Sharma, Niraj K. |
collection | PubMed |
description | OBJECTIVE: To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data. METHOD: Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert EEG reviewers independently classified one hundred IED events into IED classes or non-IEDs. First, we determined whether WC-human agreement variability falls within inter-reviewer agreement variability by calculating the variation of information for each classifier pair and quantifying the overlap between all WC-reviewer and all reviewer-reviewer pairs. Second, we compared WC and EEG reviewers’ spike identification and individual spike class labels visually and quantitatively. RESULTS: The overlap between all WC-human pairs and all human pairs was >80% for 3/5 patients and >58% for the other 2 patients demonstrating WC falling within inter-human variation. The average sensitivity of spike marking for WC was 91% and >87% for all three EEG reviewers. Finally, there was a strong visual and quantitative similarity between WC and EEG reviewers. CONCLUSIONS: WC performance is indistinguishable to that of EEG reviewers’ suggesting it could be a valid clinical tool for the assessment of IEDs. SIGNIFICANCE: WC can be used to provide quantitative analysis of epileptic spikes. |
format | Online Article Text |
id | pubmed-5476904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-54769042017-07-01 A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers Sharma, Niraj K. Pedreira, Carlos Centeno, Maria Chaudhary, Umair J. Wehner, Tim França, Lucas G.S. Yadee, Tinonkorn Murta, Teresa Leite, Marco Vos, Sjoerd B. Ourselin, Sebastien Diehl, Beate Lemieux, Louis Clin Neurophysiol Article OBJECTIVE: To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data. METHOD: Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert EEG reviewers independently classified one hundred IED events into IED classes or non-IEDs. First, we determined whether WC-human agreement variability falls within inter-reviewer agreement variability by calculating the variation of information for each classifier pair and quantifying the overlap between all WC-reviewer and all reviewer-reviewer pairs. Second, we compared WC and EEG reviewers’ spike identification and individual spike class labels visually and quantitatively. RESULTS: The overlap between all WC-human pairs and all human pairs was >80% for 3/5 patients and >58% for the other 2 patients demonstrating WC falling within inter-human variation. The average sensitivity of spike marking for WC was 91% and >87% for all three EEG reviewers. Finally, there was a strong visual and quantitative similarity between WC and EEG reviewers. CONCLUSIONS: WC performance is indistinguishable to that of EEG reviewers’ suggesting it could be a valid clinical tool for the assessment of IEDs. SIGNIFICANCE: WC can be used to provide quantitative analysis of epileptic spikes. Elsevier 2017-07 /pmc/articles/PMC5476904/ /pubmed/28531810 http://dx.doi.org/10.1016/j.clinph.2017.04.016 Text en © 2017 International Federation of Clinical Neurophysiology. Elsevier Ireland Ltd. All rights reserved. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sharma, Niraj K. Pedreira, Carlos Centeno, Maria Chaudhary, Umair J. Wehner, Tim França, Lucas G.S. Yadee, Tinonkorn Murta, Teresa Leite, Marco Vos, Sjoerd B. Ourselin, Sebastien Diehl, Beate Lemieux, Louis A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
title | A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
title_full | A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
title_fullStr | A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
title_full_unstemmed | A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
title_short | A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
title_sort | novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5476904/ https://www.ncbi.nlm.nih.gov/pubmed/28531810 http://dx.doi.org/10.1016/j.clinph.2017.04.016 |
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