Study protocol: retrospectively mining multisite clinical data to presymptomatically predict seizure onset for individual patients with Sturge-Weber.

Vedmurthy, Pooja; Pinto, Anna L R; Lin, Doris D M; Comi, Anne M; Ou, Yangming

Vedmurthy, Pooja; Pinto, Anna L R; Lin, Doris D M; Comi, Anne M; Ou, Yangming.

Afiliação

Vedmurthy P; Department of Neurology and Developmental Medicine, Hugo Moser Research Institute, Baltimore, Maryland, USA.
Pinto ALR; Department of Neurology and Pediatrics, Kennedy Krieger Institute, Baltimore, MD, USA.
Lin DDM; Department of Neurology, Division of Epilepsy, Harvard Medical School, Boston, Massachusetts, USA.
Comi AM; Neuroradiology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Ou Y; Department of Neurology and Developmental Medicine, Hugo Moser Research Institute, Baltimore, Maryland, USA.

BMJ Open ; 12(2): e053103, 2022 Feb 04.

Article em En | MEDLINE | ID: mdl-35121603

Assuntos

Síndrome de Sturge-Weber; Criança; Humanos; Recém-Nascido; Neuroimagem; Estudos Prospectivos; Estudos Retrospectivos; Convulsões/diagnóstico; Convulsões/etiologia; Síndrome de Sturge-Weber/complicações; Síndrome de Sturge-Weber/diagnóstico; Síndrome de Sturge-Weber/terapia

Palavras-chave

anti-epilepsy drugs; machine learning; neuroimaging biomarker; pre-symptomatic treatment; sturge-weber syndrome

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome de Sturge-Weber Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Humans / Newborn Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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