Early detection of COPD patients' symptoms with personal environmental sensors: a remote sensing framework using probabilistic latent component analysis with linear dynamic systems.

Kolozali, Sefki; Chatzidiakou, Lia; Jones, Roderic; Quint, Jennifer K; Kelly, Frank; Barratt, Benjamin

Kolozali, Sefki; Chatzidiakou, Lia; Jones, Roderic; Quint, Jennifer K; Kelly, Frank; Barratt, Benjamin.

Afiliação

Kolozali S; School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.
Chatzidiakou L; Department of Chemistry, University of Cambridge, Cambridge, UK.
Jones R; Department of Chemistry, University of Cambridge, Cambridge, UK.
Quint JK; Faculty of Medicine, National Heart and Lung Institute, Imperial College London, London, UK.
Kelly F; Faculty of Medicine, School of Public Health, Imperial College London, London, UK.
Barratt B; Faculty of Medicine, School of Public Health, Imperial College London, London, UK.

Neural Comput Appl ; 35(23): 17247-17265, 2023.

Article em En | MEDLINE | ID: mdl-37455834

Palavras-chave

Chronic obstructive pulmonary disease (COPD); Internet of things (IoT) in Healthcare; Personal air pollution exposure; Probabilistic latent models; Remote monitoring systems

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Idioma: En Revista: Neural Comput Appl Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

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