Development of childhood asthma prediction models using machine learning approaches.

Kothalawala, Dilini M; Murray, Clare S; Simpson, Angela; Custovic, Adnan; Tapper, William J; Arshad, S Hasan; Holloway, John W; Rezwan, Faisal I

Kothalawala, Dilini M; Murray, Clare S; Simpson, Angela; Custovic, Adnan; Tapper, William J; Arshad, S Hasan; Holloway, John W; Rezwan, Faisal I.

Afiliación

Kothalawala DM; Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.
Murray CS; NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK.
Simpson A; Division of Infection, Immunity, and Respiratory Medicine, School of Biological Sciences, University of Manchester, Manchester University Hospital NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
Custovic A; Division of Infection, Immunity, and Respiratory Medicine, School of Biological Sciences, University of Manchester, Manchester University Hospital NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
Tapper WJ; National Heart and Lung Institute, Imperial College of Science, Technology, and Medicine, London, UK.
Arshad SH; Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.
Holloway JW; NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK.
Rezwan FI; The David Hide Asthma and Allergy Research Centre, St. Mary's Hospital, Isle of Wight, UK.

Clin Transl Allergy ; 11(9): e12076, 2021 Nov.

Article en En | MEDLINE | ID: mdl-34841728

Palabras clave

Asthma; Kindheit; Prognose; asthma; childhood; machine learning; maschinelles Lernen; prediction

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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Clin Transl Allergy Año: 2021 Tipo del documento: Article

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