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@@ -7,40 +7,54 @@
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# if possible, including the prefix to indicate its type.
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authors:
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-
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- firstname: "GivenName1"
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- lastname: "FamilyName1"
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- affiliation: "Affiliation1"
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- id: "ORCID:0000-0001-2345-6789"
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+ firstname: "Jan"
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+ lastname: "Yperman"
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+ affiliation: "Hasselt University, Belgium"
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+ id: "0000-0002-7632-2001"
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-
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- firstname: "GivenName2"
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- lastname: "FamilyName2"
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- affiliation: "Affiliation2"
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- id: "ResearcherID:X-1234-5678"
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+ firstname: "Veronica"
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+ lastname: "Popescu"
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+ affiliation: "Hasselt University, Belgium"
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-
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- firstname: "GivenName3"
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- lastname: "FamilyName3"
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+ firstname: "Bart"
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+ lastname: "Van Wijmeersch"
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+ affiliation: "Hasselt University, Belgium"
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+ -
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+ firstname: "Thijs"
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+ lastname: "Becker"
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+ affiliation: "Hasselt University, Belgium"
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+ -
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+ firstname: "Liesbet"
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+ lastname: "Peeters"
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+ affiliation: "Hasselt University, Belgium"
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# A title to describe the published resource.
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-title: "Example Title"
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+title: "Motor evoked potentials for multiple sclerosis: A multiyear follow-up dataset."
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# Additional information about the resource, e.g., a brief abstract.
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description: |
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- Example description
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- that can contain linebreaks
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- but has to maintain indentation.
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+ Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. The signal conduction through the central
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+ nervous system of MS patients deteriorates. Evoked potential measurements allow clinicians to monitor the degree of
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+ deterioration and are used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements,
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+ in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100
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+ milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset consists of 5586 visits of
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+ 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000
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+ MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used
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+ to explore the role of evoked potentials in MS research and patient care. It may also be used as a real-world benchmark for
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+ machine learning techniques for time series analysis and predictive modelling.
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# Lit of keywords the resource should be associated with.
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# Give as many keywords as possible, to make the resource findable.
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keywords:
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- - Neuroscience
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- - Keyword2
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- - Keyword3
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+ - Multiple Sclerosis
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+ - Prognosis
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+ - Time series
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# License information for this resource. Please provide the license name and/or a link to the license.
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# Please add also a corresponding LICENSE file to the repository.
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license:
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- name: "Creative Commons CC0 1.0 Public Domain Dedication"
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- url: "https://creativecommons.org/publicdomain/zero/1.0/"
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+ name: "CC-BY"
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+ url: "https://creativecommons.org/licenses/by/4.0/"
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@@ -49,8 +63,8 @@ license:
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# Funding information for this resource.
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# Separate funder name and grant number by comma.
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funding:
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- - "DFG, AB1234/5-6"
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- - "EU, EU.12345"
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+ # - "DFG, AB1234/5-6"
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+ # - "EU, EU.12345"
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# Related publications. reftype might be: IsSupplementTo, IsDescribedBy, IsReferencedBy.
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@@ -60,17 +74,13 @@ funding:
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# In the citation field, please provide the full reference, including title, authors, journal etc.
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references:
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-
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- id: "doi:10.xxx/zzzz"
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+ id: "doi:10.1186/s12883-020-01672-w"
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reftype: "IsSupplementTo"
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- citation: "Citation1"
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+ citation: "Yperman, J., Becker, T., Valkenborg, D., Popescu, V., Hellings, N., Wijmeersch, B. V., & Peeters, L. M. (2020). Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis. BMC Neurology, 20(1)."
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-
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- id: "arxiv:mmmm.nnnn"
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+ id: "doi:10.3389/fninf.2020.00028"
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reftype: "IsSupplementTo"
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- citation: "Citation2"
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- -
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- id: "pmid:nnnnnnnn"
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- reftype: "IsReferencedBy"
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- citation: "Citation3"
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+ citation: "Yperman, J., Becker, T., Valkenborg, D., Hellings, N., Cambron, M., Dive, D., Laureys, G., Popescu, V., Van Wijmeersch, B., & Peeters, L. M. (2020). Deciphering the Morphology of Motor Evoked Potentials. Frontiers in Neuroinformatics, 14."
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# Resource type. Default is Dataset, other possible values are Software, DataPaper, Image, Text.
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