The goal of this observational study is to test whether it is possible to detect particular lung sounds that are unique to patients with the lung disease pulmonary fibrosis and whether any such sounds could be analysed using machine learning to make diagnosing disease easier. Participants will have a sound detection device placed in different locations on the chest and audio sounds will be recorded for analysis. Researchers will compare audio recordings from clinically diagnosed patients with recordings from healthy controls of a similar age to see whether the sounds are sufficiently different within that age group.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Number of clinical lung sound recordings stored from pulmonary fibrosis cases and controls
Timeframe: 6 months
Measure of ability of this system to classify participants as PF patients or healthy controls
Timeframe: 8 months
Feedback from patients and study clinicians
Timeframe: 8 months