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Updated: Jan 10, 2026

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
A qualitative interview study to investigate opportunities for improvement in routine asthma care using a clinical
Holly Tibble1, Jaime Garcia Iglesias2, Alexandria Chung3
1Usher Institute, The University of Edinburgh, Edinburgh, UK. htibble@ed.ac.uk.
Abstract:
More than 8 million people in the UK have been diagnosed with asthma, a chronic respiratory condition which leads to the death of more than 25 people per week. Clinical decision support software (CDSS) can be used to improve patient care by improving clinical accuracy or by increasing the efficiency of clinical practice. This study aimed to identify desired functionalities of a software tool for asthma care, from both primary and specialist health care providers. Qualitative data were collected from semi-structured interviews with 19 participants. Eight functionalities were identified for prioritisation for the development of clinical decision support system in asthma, including diagnosis support, medical history retrieval, and adherence to best practice guidelines. Parallels were drawn with successful CDSS applications in other medical fields, such as radiology, highlighting the value of interdisciplinary learning and adaptation. Prioritising user-centred design, and aligning processes with existing workflows, may allow software tools to lighten administrative burdens, promote proactive patient care, and improve patient outcomes. Healthcare software development must focus on creating tools which are intuitive, reliable, and co-designed, in order to increase uptake and sustained impact.
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