Detecting asthma exacerbations using daily home monitoring and machine learning.

Zhang, Olivier; Minku, Leandro L; Gonem, Sherif

Zhang, Olivier; Minku, Leandro L; Gonem, Sherif.

Affiliation

Zhang O; Department of Computer Engineering (INFO), INSA Rennes, Rennes, France.
Minku LL; School of Computer Science, University of Birmingham, UK.
Gonem S; Department of Respiratory Medicine, Nottingham City Hospital, Nottingham, UK.

J Asthma ; 58(11): 1518-1527, 2021 11.

Article in En | MEDLINE | ID: mdl-32718193

Subject(s)

Asthma/diagnosis; Asthma/drug therapy; Bronchodilator Agents/administration & dosage; Budesonide/administration & dosage; Disease Progression; Formoterol Fumarate/administration & dosage; Home Care Services; Machine Learning; Monitoring, Physiologic; Terbutaline/administration & dosage; Drug Combinations; Female; Humans; Male; Middle Aged; Severity of Illness Index

Key words

Asthma; exacerbation; home monitoring; machine learning; peak expiratory flow

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Asthma / Terbutaline / Bronchodilator Agents / Disease Progression / Budesonide / Formoterol Fumarate / Machine Learning / Home Care Services / Monitoring, Physiologic Type of study: Clinical_trials / Prognostic_studies / Screening_studies Limits: Female / Humans / Male / Middle aged Language: En Journal: J Asthma Year: 2021 Type: Article Affiliation country: France

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