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Identification by cluster analysis of patients with asthma and nasal symptoms u...

Bousquet, J.; Sousa-Pinto, B.; Anto, J. M.; Amaral, R.; Brussino, L.; Canonica, G. W.; Cruz, A. A.; Gemicioglu, B.; Haahtela, T.; Kupczyk, M.

Background: The self-reporting of asthma frequently leads to patient misidentification in epidemiological studies. Strategies combining the triangulation of data sources may help to improve the identification of people with asthma. We aimed to combine information from the self-reporting of asthma, medication use and symptoms to identify asthma patterns in the users of an mHealth app. Methods: We studied MASK-ai...

Date: 2023   |   Origin: Estudo Geral - Universidade de Coimbra
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