OpenAccessBelV2, Main, Exploration, bibRecord, 000076

Crowdsourcing reproducible seizure forecasting in human and canine epilepsy.

Identifieur interne : 000076 ( Main/Exploration ); précédent : 000075; suivant : 000077

Crowdsourcing reproducible seizure forecasting in human and canine epilepsy.

Auteurs : Benjamin H. Brinkmann [États-Unis] ; Joost Wagenaar [États-Unis] ; Drew Abbot [États-Unis] ; Phillip Adkins [États-Unis] ; Simone C. Bosshard [Australie] ; Min Chen [Australie] ; Quang M. Tieng [Australie] ; Jialune He [États-Unis] ; F J Mu Oz-Almaraz [Espagne] ; Paloma Botella-Rocamora [Espagne] ; Juan Pardo [Espagne] ; Francisco Zamora-Martinez [Espagne] ; Michael Hills [Australie] ; Wei Wu [États-Unis] ; Iryna Korshunova [Belgique] ; Will Cukierski [États-Unis] ; Charles Vite [États-Unis] ; Edward E. Patterson [États-Unis] ; Brian Litt [États-Unis] ; Gregory A. Worrell [États-Unis]

Source :

Brain : a journal of neurology [ 1460-2156 ] ; 2016.

RBID : pubmed:27034258

Abstract

SEE MORMANN AND ANDRZEJAK DOI101093/BRAIN/AWW091 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE : Accurate forecasting of epileptic seizures has the potential to transform clinical epilepsy care. However, progress toward reliable seizure forecasting has been hampered by lack of open access to long duration recordings with an adequate number of seizures for investigators to rigorously compare algorithms and results. A seizure forecasting competition was conducted on kaggle.com using open access chronic ambulatory intracranial electroencephalography from five canines with naturally occurring epilepsy and two humans undergoing prolonged wide bandwidth intracranial electroencephalographic monitoring. Data were provided to participants as 10-min interictal and preictal clips, with approximately half of the 60 GB data bundle labelled (interictal/preictal) for algorithm training and half unlabelled for evaluation. The contestants developed custom algorithms and uploaded their classifications (interictal/preictal) for the unknown testing data, and a randomly selected 40% of data segments were scored and results broadcasted on a public leader board. The contest ran from August to November 2014, and 654 participants submitted 17 856 classifications of the unlabelled test data. The top performing entry scored 0.84 area under the classification curve. Following the contest, additional held-out unlabelled data clips were provided to the top 10 participants and they submitted classifications for the new unseen data. The resulting area under the classification curves were well above chance forecasting, but did show a mean 6.54 ± 2.45% (min, max: 0.30, 20.2) decline in performance. The kaggle.com model using open access data and algorithms generated reproducible research that advanced seizure forecasting. The overall performance from multiple contestants on unseen data was better than a random predictor, and demonstrates the feasibility of seizure forecasting in canine and human epilepsy.media-1vid110.1093/brain/aww045_video_abstractaww045_video_abstract.

DOI: 10.1093/brain/aww045
PubMed: 27034258

Affiliations:

Le document en format XML

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<author><name sortKey="Tieng, Quang M" sort="Tieng, Quang M" uniqKey="Tieng Q" first="Quang M" last="Tieng">Quang M. Tieng</name>
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<author><name sortKey="Mu Oz Almaraz, F J" sort="Mu Oz Almaraz, F J" uniqKey="Mu Oz Almaraz F" first="F J" last="Mu Oz-Almaraz">F J Mu Oz-Almaraz</name>
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<author><name sortKey="Zamora Martinez, Francisco" sort="Zamora Martinez, Francisco" uniqKey="Zamora Martinez F" first="Francisco" last="Zamora-Martinez">Francisco Zamora-Martinez</name>
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<author><name sortKey="Hills, Michael" sort="Hills, Michael" uniqKey="Hills M" first="Michael" last="Hills">Michael Hills</name>
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<author><name sortKey="Wu, Wei" sort="Wu, Wei" uniqKey="Wu W" first="Wei" last="Wu">Wei Wu</name>
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<author><name sortKey="Korshunova, Iryna" sort="Korshunova, Iryna" uniqKey="Korshunova I" first="Iryna" last="Korshunova">Iryna Korshunova</name>
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<author><name sortKey="Cukierski, Will" sort="Cukierski, Will" uniqKey="Cukierski W" first="Will" last="Cukierski">Will Cukierski</name>
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<author><name sortKey="Vite, Charles" sort="Vite, Charles" uniqKey="Vite C" first="Charles" last="Vite">Charles Vite</name>
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<author><name sortKey="Patterson, Edward E" sort="Patterson, Edward E" uniqKey="Patterson E" first="Edward E" last="Patterson">Edward E. Patterson</name>
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<author><name sortKey="Litt, Brian" sort="Litt, Brian" uniqKey="Litt B" first="Brian" last="Litt">Brian Litt</name>
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<author><name sortKey="Worrell, Gregory A" sort="Worrell, Gregory A" uniqKey="Worrell G" first="Gregory A" last="Worrell">Gregory A. Worrell</name>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Crowdsourcing reproducible seizure forecasting in human and canine epilepsy.</title>
<author><name sortKey="Brinkmann, Benjamin H" sort="Brinkmann, Benjamin H" uniqKey="Brinkmann B" first="Benjamin H" last="Brinkmann">Benjamin H. Brinkmann</name>
<affiliation wicri:level="2"><nlm:affiliation>Mayo Systems Electrophysiology Laboratory, Departments of Neurology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA Brinkmann.Benjamin@mayo.edu.</nlm:affiliation>
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<author><name sortKey="Wagenaar, Joost" sort="Wagenaar, Joost" uniqKey="Wagenaar J" first="Joost" last="Wagenaar">Joost Wagenaar</name>
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<country xml:lang="fr">États-Unis</country>
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<author><name sortKey="Abbot, Drew" sort="Abbot, Drew" uniqKey="Abbot D" first="Drew" last="Abbot">Drew Abbot</name>
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<author><name sortKey="Adkins, Phillip" sort="Adkins, Phillip" uniqKey="Adkins P" first="Phillip" last="Adkins">Phillip Adkins</name>
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<country xml:lang="fr">États-Unis</country>
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<author><name sortKey="Bosshard, Simone C" sort="Bosshard, Simone C" uniqKey="Bosshard S" first="Simone C" last="Bosshard">Simone C. Bosshard</name>
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<country xml:lang="fr">Australie</country>
<wicri:regionArea>University of Queensland, Centre for Advanced Imaging, Queensland</wicri:regionArea>
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<author><name sortKey="Chen, Min" sort="Chen, Min" uniqKey="Chen M" first="Min" last="Chen">Min Chen</name>
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<country xml:lang="fr">Australie</country>
<wicri:regionArea>University of Queensland, Centre for Advanced Imaging, Queensland</wicri:regionArea>
<wicri:noRegion>Queensland</wicri:noRegion>
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<author><name sortKey="Tieng, Quang M" sort="Tieng, Quang M" uniqKey="Tieng Q" first="Quang M" last="Tieng">Quang M. Tieng</name>
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<country xml:lang="fr">Australie</country>
<wicri:regionArea>University of Queensland, Centre for Advanced Imaging, Queensland</wicri:regionArea>
<wicri:noRegion>Queensland</wicri:noRegion>
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<author><name sortKey="He, Jialune" sort="He, Jialune" uniqKey="He J" first="Jialune" last="He">Jialune He</name>
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<placeName><region type="state">Massachusetts</region>
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<author><name sortKey="Mu Oz Almaraz, F J" sort="Mu Oz Almaraz, F J" uniqKey="Mu Oz Almaraz F" first="F J" last="Mu Oz-Almaraz">F J Mu Oz-Almaraz</name>
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<author><name sortKey="Botella Rocamora, Paloma" sort="Botella Rocamora, Paloma" uniqKey="Botella Rocamora P" first="Paloma" last="Botella-Rocamora">Paloma Botella-Rocamora</name>
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<author><name sortKey="Pardo, Juan" sort="Pardo, Juan" uniqKey="Pardo J" first="Juan" last="Pardo">Juan Pardo</name>
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<author><name sortKey="Zamora Martinez, Francisco" sort="Zamora Martinez, Francisco" uniqKey="Zamora Martinez F" first="Francisco" last="Zamora-Martinez">Francisco Zamora-Martinez</name>
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<author><name sortKey="Hills, Michael" sort="Hills, Michael" uniqKey="Hills M" first="Michael" last="Hills">Michael Hills</name>
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<author><name sortKey="Wu, Wei" sort="Wu, Wei" uniqKey="Wu W" first="Wei" last="Wu">Wei Wu</name>
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<placeName><region type="state">État de New York</region>
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<author><name sortKey="Korshunova, Iryna" sort="Korshunova, Iryna" uniqKey="Korshunova I" first="Iryna" last="Korshunova">Iryna Korshunova</name>
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<author><name sortKey="Cukierski, Will" sort="Cukierski, Will" uniqKey="Cukierski W" first="Will" last="Cukierski">Will Cukierski</name>
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<author><name sortKey="Vite, Charles" sort="Vite, Charles" uniqKey="Vite C" first="Charles" last="Vite">Charles Vite</name>
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<country xml:lang="fr">États-Unis</country>
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<author><name sortKey="Patterson, Edward E" sort="Patterson, Edward E" uniqKey="Patterson E" first="Edward E" last="Patterson">Edward E. Patterson</name>
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<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>University of Minnesota, Veterinary Medical Center, St. Paul, MN</wicri:regionArea>
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<author><name sortKey="Litt, Brian" sort="Litt, Brian" uniqKey="Litt B" first="Brian" last="Litt">Brian Litt</name>
<affiliation wicri:level="2"><nlm:affiliation>University of Pennsylvania, Penn Center for Neuroengineering and Therapeutics, Philadelphia, PA, USA.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>University of Pennsylvania, Penn Center for Neuroengineering and Therapeutics, Philadelphia, PA</wicri:regionArea>
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<author><name sortKey="Worrell, Gregory A" sort="Worrell, Gregory A" uniqKey="Worrell G" first="Gregory A" last="Worrell">Gregory A. Worrell</name>
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<country xml:lang="fr">États-Unis</country>
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<front><div type="abstract" xml:lang="en">SEE MORMANN AND ANDRZEJAK DOI101093/BRAIN/AWW091 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE  : Accurate forecasting of epileptic seizures has the potential to transform clinical epilepsy care. However, progress toward reliable seizure forecasting has been hampered by lack of open access to long duration recordings with an adequate number of seizures for investigators to rigorously compare algorithms and results. A seizure forecasting competition was conducted on kaggle.com using open access chronic ambulatory intracranial electroencephalography from five canines with naturally occurring epilepsy and two humans undergoing prolonged wide bandwidth intracranial electroencephalographic monitoring. Data were provided to participants as 10-min interictal and preictal clips, with approximately half of the 60 GB data bundle labelled (interictal/preictal) for algorithm training and half unlabelled for evaluation. The contestants developed custom algorithms and uploaded their classifications (interictal/preictal) for the unknown testing data, and a randomly selected 40% of data segments were scored and results broadcasted on a public leader board. The contest ran from August to November 2014, and 654 participants submitted 17 856 classifications of the unlabelled test data. The top performing entry scored 0.84 area under the classification curve. Following the contest, additional held-out unlabelled data clips were provided to the top 10 participants and they submitted classifications for the new unseen data. The resulting area under the classification curves were well above chance forecasting, but did show a mean 6.54 ± 2.45% (min, max: 0.30, 20.2) decline in performance. The kaggle.com model using open access data and algorithms generated reproducible research that advanced seizure forecasting. The overall performance from multiple contestants on unseen data was better than a random predictor, and demonstrates the feasibility of seizure forecasting in canine and human epilepsy.media-1vid110.1093/brain/aww045_video_abstractaww045_video_abstract.</div>
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<name sortKey="Litt, Brian" sort="Litt, Brian" uniqKey="Litt B" first="Brian" last="Litt">Brian Litt</name>
<name sortKey="Patterson, Edward E" sort="Patterson, Edward E" uniqKey="Patterson E" first="Edward E" last="Patterson">Edward E. Patterson</name>
<name sortKey="Vite, Charles" sort="Vite, Charles" uniqKey="Vite C" first="Charles" last="Vite">Charles Vite</name>
<name sortKey="Wagenaar, Joost" sort="Wagenaar, Joost" uniqKey="Wagenaar J" first="Joost" last="Wagenaar">Joost Wagenaar</name>
<name sortKey="Worrell, Gregory A" sort="Worrell, Gregory A" uniqKey="Worrell G" first="Gregory A" last="Worrell">Gregory A. Worrell</name>
<name sortKey="Wu, Wei" sort="Wu, Wei" uniqKey="Wu W" first="Wei" last="Wu">Wei Wu</name>
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<country name="Australie"><noRegion><name sortKey="Bosshard, Simone C" sort="Bosshard, Simone C" uniqKey="Bosshard S" first="Simone C" last="Bosshard">Simone C. Bosshard</name>
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<name sortKey="Chen, Min" sort="Chen, Min" uniqKey="Chen M" first="Min" last="Chen">Min Chen</name>
<name sortKey="Hills, Michael" sort="Hills, Michael" uniqKey="Hills M" first="Michael" last="Hills">Michael Hills</name>
<name sortKey="Tieng, Quang M" sort="Tieng, Quang M" uniqKey="Tieng Q" first="Quang M" last="Tieng">Quang M. Tieng</name>
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<country name="Espagne"><noRegion><name sortKey="Mu Oz Almaraz, F J" sort="Mu Oz Almaraz, F J" uniqKey="Mu Oz Almaraz F" first="F J" last="Mu Oz-Almaraz">F J Mu Oz-Almaraz</name>
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<name sortKey="Pardo, Juan" sort="Pardo, Juan" uniqKey="Pardo J" first="Juan" last="Pardo">Juan Pardo</name>
<name sortKey="Zamora Martinez, Francisco" sort="Zamora Martinez, Francisco" uniqKey="Zamora Martinez F" first="Francisco" last="Zamora-Martinez">Francisco Zamora-Martinez</name>
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<country name="Belgique"><noRegion><name sortKey="Korshunova, Iryna" sort="Korshunova, Iryna" uniqKey="Korshunova I" first="Iryna" last="Korshunova">Iryna Korshunova</name>
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Crowdsourcing reproducible seizure forecasting in human and canine epilepsy.

Crowdsourcing reproducible seizure forecasting in human and canine epilepsy.

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