ArticleBreathe (Sheffield, England)2025
Innovation in technologies for monitoring lung function in patients with respiratory disease.
Article in Breathe (Sheffield, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
Pulmonary function testing is a pillar of respiratory medicine, contributing to the diagnosis and monitoring of respiratory diseases and supporting therapeutic decisions. The aim of this review is to summarise advances in the field of lung function monitoring, presenting both innovation in current everyday lung function testing, as well as newer physiological and functional imaging techniques. We highlight the potential clinical utility of novel digital tools, such as smart inhalers, wearables and sensors, that enable continuous real-time monitoring of lung physiological parameters and assessment of therapeutic interventions. Finally, current evidence for the application of artificial intelligence tools, such as machine- and deep-learning algorithms, in lung function interpretation is discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.