Brainomix, a leading provider of Artificial Intelligence (AI) solutions, has recently announced its involvement in a new study backed by the University of Liverpool. The study aims to assess the clinical effectiveness, cost-effectiveness and acceptability of Huawei Smartwear to detect post-stroke Atrial Fibrillation (AF). Sites with existing clinical deployments of Brainomix’s e-Stroke platform will utilize the AI system to collect real-time imaging data and securely transfer them to the central investigators.
Chief Investigator Gregory Lip of the Liverpool Centre for Cardiovascular Science is leading the Liverpool Huawei Stroke Study. “We are delighted by this collaboration with Brainomix, which enhances our growing research portfolio into stroke and atrial fibrillation research and would help inform clinical practice and improve our care and management of these patients,” said Lip.
The hope is that the new study will result in earlier detection of AF, which could reduce the risk of recurrent stroke in post-stroke populations. Brainomix’s AI system will provide a secure and automated platform for collecting imaging data, allowing for the rapid assessment of large numbers of patients.
The collaboration between Brainomix and the University of Liverpool is a major step forward in stroke research. AI systems like Brainomix’s e-Stroke platform enable medical professionals to diagnose more precisely and accurately. This, in turn, has led to the development of better treatments and improved outcomes for stroke patients.
In addition to providing data collection services, Brainomix also offers AI-powered clinical decision support tools. These tools can help medical professionals make better and faster decisions in treating stroke and other neurological conditions.
By leveraging the power of AI, Brainomix can help healthcare providers identify at-risk patients, provide more personalized care and deliver more effective and cost-efficient treatments. The collaboration between Brainomix and the University of Liverpool is a noteworthy example of how AI is being used to improve the quality of healthcare and patient outcomes.