SPS academics help East Kent hospitals improve patient care with artificial intelligence

School continues to build on excellent track record in medical imaging with game-changing computer software

SPS has worked with doctors to develop artificial intelligence computer software that can detect signs of eye disease earlier and improve patient care and outcomes.

Patients at East Kent Hospitals can now have their eye health monitored by a computer thanks to new software developed by Dr. Stuart Gibson in collaboration with doctors at the Trust.

The new artificial intelligence computer software compares new images of the eye with a patient’s previous photographs to detect clinical signs, and will alert a doctor if their condition has worsened.

Senior lecturer Dr Stuart Gibson said: “AI has completely revolutionised the way we approach computer vision research. Our team has considerable experience in this area, having previously developed AI for facial identification, detection of objects concealed in postal items and the identification of unknown substances.

“The primary motivation for our work is to have a positive impact on society. Our project with Nishal Patel and the Trust has the potential to significantly improve patient care.”

Dr. Stuart Gibson

Nishal Patel, an Ophthalmology Consultant at the Trust, who also holds a teaching position at the University, said it opened up a wealth of opportunities for the future.

He said: “We are seeing more and more people with retinal disease and machines can help with some of the capacity issues faced by our department and others across the country. We are not taking the job of a doctor away, but we are making it more efficient and at the same time helping determine how artificial intelligence will shape the future medicine.

“By automating some of the decisions, so that stable patients can be monitored and unstable patients treated earlier, we can offer better outcomes for our patients.”

Nishal Patel, an Ophthalmology Consultant at the Trust

The software prompts clinicians to act if a patient’s condition has worsened, but removes the need for a face-to-face consultation if nothing has changed.

It means virtual clinics can be introduced, freeing up consultant time for patients with more complicated or serious conditions.

But doctors will be alerted automatically if the images reveal any changes and patients will be invited to see the team in person.

Mr Patel said: “This system gives us the ability to investigate machine learning outcomes without involving commercial organisations, thanks to our collaboration with the university.”

This work builds on our teams strong track record in medical imaging, which spans 30 years and includes being a pioneer of the technique that underpins the ophthalmology systems now used regularly in hospitals around the world.

The School is currently offering a PhD studentship in this area. Find out more here.