Wellbeing Software has partnered with AI Specialist Brainomix to accelerate the introduction of AI and deep learning to assist clinical decision making for ischemic stroke patients.
The Brainomix solution utilises Artificial Intelligence, deep learning algorithms and clinical engineering to assist healthcare professionals with imaging decision support.
When a patient is admitted to hospital with a suspected ischemic stroke, they undergo a CT scan to confirm or rule out a diagnosis. Patients are then assessed to receive treatment such as thrombolysis, endovascular treatment or for severe cases, decompressive craniectomy. These treatments are time-sensitive, and decisions must be made within the first few hours to ensure the best possible outcome.
Brainomix’s E-ASPECTS solution is designed to assist healthcare professionals to make quick, informed decisions by applying AI when assessing ischemic stroke damage.
It interprets scans based on metrics drawn from over 150,000 images, sourced across 27 countries including UK, Germany, Spain, Italy and the United States.
Chris Yeowart, Director at Wellbeing Software said “Working with innovative companies like Brainomix represents a real opportunity for the NHS to access transformative AI technology, and to embed it quickly and easily into their everyday workflow through our vendor neutral gateway. We are actively engaged in a ground-breaking regional project with Brainomix which we look forward to announcing shortly.”
Riaz Rahman, VP Healthcare Global at Brainomix, said “Early intervention is key to improve recovery following an ischemic stroke. By applying AI and deep learning, clinicians are able to make informed decisions regarding treatment, reducing the chances of further brain damage or mortalities. As the market leader in Radiology Information Systems (RIS), Wellbeing is well placed to accelerate the integration of AI and deep learning in the NHS.”
In a recent research study from Wellbeing, they found that 85% of respondents acknowledged the benefits of AI integration within RIS workflow, including its ability to support work management and report prioritisation, especially the notification of critical findings.
