datacite.yml 4.2 KB

  1. # Metadata for DOI registration according to DataCite Metadata Schema 4.1.
  2. # For detailed schema description see
  3. ## Required fields
  4. # The main researchers involved. Include digital identifier (e.g., ORCID)
  5. # if possible, including the prefix to indicate its type.
  6. authors:
  7. -
  8. firstname: "Jan"
  9. lastname: "Yperman"
  10. affiliation: "Hasselt University, Belgium"
  11. id: "0000-0002-7632-2001"
  12. -
  13. firstname: "Veronica"
  14. lastname: "Popescu"
  15. affiliation: "Hasselt University, Belgium"
  16. -
  17. firstname: "Bart"
  18. lastname: "Van Wijmeersch"
  19. affiliation: "Hasselt University, Belgium"
  20. -
  21. firstname: "Thijs"
  22. lastname: "Becker"
  23. affiliation: "Hasselt University, Belgium"
  24. -
  25. firstname: "Liesbet"
  26. lastname: "Peeters"
  27. affiliation: "Hasselt University, Belgium"
  28. # A title to describe the published resource.
  29. title: "Motor evoked potentials for multiple sclerosis: A multiyear follow-up dataset."
  30. # Additional information about the resource, e.g., a brief abstract.
  31. description: |
  32. Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. The signal conduction through the central
  33. nervous system of MS patients deteriorates. Evoked potential measurements allow clinicians to monitor the degree of
  34. deterioration and are used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements,
  35. in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100
  36. milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset consists of 5586 visits of
  37. 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000
  38. MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used
  39. to explore the role of evoked potentials in MS research and patient care. It may also be used as a real-world benchmark for
  40. machine learning techniques for time series analysis and predictive modelling.
  41. # Lit of keywords the resource should be associated with.
  42. # Give as many keywords as possible, to make the resource findable.
  43. keywords:
  44. - Multiple Sclerosis
  45. - Prognosis
  46. - Time series
  47. # License information for this resource. Please provide the license name and/or a link to the license.
  48. # Please add also a corresponding LICENSE file to the repository.
  49. license:
  50. name: "CC-BY"
  51. url: ""
  52. ## Optional Fields
  53. # Funding information for this resource.
  54. # Separate funder name and grant number by comma.
  55. funding:
  56. - "The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation—Flanders (FWO) and the Flemish Government—department EWI."
  57. - "Research Foundation—Flanders (FWO) for ELIXIR Belgium (I002819N), and Hermesfonds for ELIXIR Belgium, AH.2017.051, IO 17001306"
  58. # Related publications. reftype might be: IsSupplementTo, IsDescribedBy, IsReferencedBy.
  59. # Please provide digital identifier (e.g., DOI) if possible.
  60. # Add a prefix to the ID, separated by a colon, to indicate the source.
  61. # Supported sources are: DOI, arXiv, PMID
  62. # In the citation field, please provide the full reference, including title, authors, journal etc.
  63. references:
  64. -
  65. id: "doi:10.1186/s12883-020-01672-w"
  66. reftype: "IsSupplementTo"
  67. 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)."
  68. -
  69. id: "doi:10.3389/fninf.2020.00028"
  70. reftype: "IsSupplementTo"
  71. 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."
  72. # Resource type. Default is Dataset, other possible values are Software, DataPaper, Image, Text.
  73. resourcetype: Dataset
  74. # Do not edit or remove the following line
  75. templateversion: 1.2