Predicting Pain in People With Sickle Cell Disease in the Day Hospital Using the Commercial Wearable Apple Watch: Feasibility Study.

Stojancic, Rebecca Sofia; Subramaniam, Arvind; Vuong, Caroline; Utkarsh, Kumar; Golbasi, Nuran; Fernandez, Olivia; Shah, Nirmish

Stojancic, Rebecca Sofia; Subramaniam, Arvind; Vuong, Caroline; Utkarsh, Kumar; Golbasi, Nuran; Fernandez, Olivia; Shah, Nirmish.

Afiliação

Stojancic RS; Duke Sickle Cell Comprehensive Care Unit, Department of Medicine, Division of Hematology, Duke University Hospital, Durham, NC, United States.
Subramaniam A; Duke Sickle Cell Comprehensive Care Unit, Department of Medicine, Division of Hematology, Duke University Hospital, Durham, NC, United States.
Vuong C; Brody School of Medicine, East Carolina University, Greenville, NC, United States.
Utkarsh K; Department of Pediatric Hematology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Golbasi N; Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, United States.
Fernandez O; Joan & Sanford I Weill Medical College, Cornell University, New York, NY, United States.
Shah N; University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

JMIR Form Res ; 7: e45355, 2023 Mar 14.

Article em En | MEDLINE | ID: mdl-36917171

Palavras-chave

Apple Watch; consumer wearable; machine learning; mobile health; pain; predict; prediction; sickle cell disease; smartwatch; vaso-occlusive crises; wearable

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Form Res Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Canadá

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