View in EDS

Response to letter to the editor: Authors response to comment on "Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features".

Saved in:
Bibliographic Details
Title: Response to letter to the editor: Authors response to comment on "Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features".
Authors: Petracca M; Department of Human Neurosciences, Sapienza University of Rome, Italy., Cocozza S; Department of Advanced Biomedical Sciences, University 'Federico II', Naples, Italy., Cuocolo R; Department of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy. Electronic address: rcuocolo@unisa.it.
Source: Journal of the neurological sciences [J Neurol Sci] 2026 Jun 15; Vol. 485, pp. 125887. Date of Electronic Publication: 2026 Mar 27.
Publication Type: Letter
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0375403 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-5883 (Electronic) Linking ISSN: 0022510X NLM ISO Abbreviation: J Neurol Sci Subsets: MEDLINE; In Process
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41912368
AccessLevel: 2
PubType: Editorial & Opinion
PubTypeId: editorialOpinion
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Response to letter to the editor: Authors response to comment on "Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features".
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Petracca+M%22">Petracca M</searchLink>; Department of Human Neurosciences, Sapienza University of Rome, Italy.<br /><searchLink fieldCode="AU" term="%22Cocozza+S%22">Cocozza S</searchLink>; Department of Advanced Biomedical Sciences, University 'Federico II', Naples, Italy.<br /><searchLink fieldCode="AU" term="%22Cuocolo+R%22">Cuocolo R</searchLink>; Department of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy. Electronic address: rcuocolo@unisa.it.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%220375403%22">Journal of the neurological sciences</searchLink> [J Neurol Sci] 2026 Jun 15; Vol. 485, pp. 125887. <i>Date of Electronic Publication: </i>2026 Mar 27.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Letter
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>0375403 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1878-5883 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%220022510X%22">0022510X </searchLink><i>NLM ISO Abbreviation: </i>J Neurol Sci <i>Subsets: </i>MEDLINE; In Process
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41912368
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.jns.2026.125887
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 125887
    Titles:
      – TitleFull: Response to letter to the editor: Authors response to comment on "Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features".
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Petracca M
      – PersonEntity:
          Name:
            NameFull: Cocozza S
      – PersonEntity:
          Name:
            NameFull: Cuocolo R
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 06
              Text: 2026 Jun 15
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1878-5883
          Numbering:
            – Type: volume
              Value: 485
          Titles:
            – TitleFull: Journal of the neurological sciences
              Type: main
ResultId 1