AI could help NHS clinicians diagnose childhood sleep apnoea
AI software designed to help diagnose sleep apnoea in children has achieved high accuracy in an NHS trial, with the findings independently reviewed by clinical specialists.
We are developing the AI data analytics platform to support neurological diagnostics.
For our AI to interpret a study, reduced from hours of expert manual analysis
Points of training data, includingbrain, heart, and muscle activity
Within first successful UK clinical study (NHS Scotland)
Hardware agnostic, ingesting datafrom existing clinical systems, & operates within current reimbursement codes
Custom AI & ML algorithms identify & highlight pathological areas within brain, heart, and muscle activity.
Highest data complexity first.AI models that works on kidsworks on adults. The reverse isnot true
We are dedicated to reducing strain on children, families, and healthcare systems through efficient diagnostics.
We are seeing how automated data analysis for diagnosis can be done safely and accurately. Where this is shown to be the case, clinicians’ time is freed up to do the jobs that require their expertise, and this takes pressure off busy departments, firefighting waitlists.
Seluna’s technology has the potential to reduce delays, improve consistency in reporting, and allow us to prioritise care for the children who most urgently need intervention.
AI software designed to help diagnose sleep apnoea in children has achieved high accuracy in an NHS trial, with the findings independently reviewed by clinical specialists.
Seluna secures nearly £650K funding to advance machine learning technology that could revolutionise diagnosis and management of childhood sleep apnoea
Yola will be driving our technological innovation, developing the cutting-edge solutions that have the potential to transform healthcare delivery.