Respiratory deterioration rarely happens without warning. The challenge is that early signals are often subtle, spread across several measurements and easy to miss in a short appointment.
Seeing patterns, not single values
AI models are well suited to recognising patterns across many parameters at once. Rather than relying on a single threshold, a model can weigh changes in amplitude, variability and composition together.
This makes it possible to flag a change in risk before symptoms become severe, giving patients and clinicians time to respond.
Supporting, not replacing, clinicians
AI-driven insight is designed to support clinical judgement. Clear, actionable outputs help healthcare professionals prioritise care and personalise treatment plans.
