Permutable is excited to announce that it has been using AI and its proprietary machine learning engine to detect heart abnormalities.
In this exciting departure from the original application of Permutable’s learning engine R2, which was in the area of financial data, this cutting edge technology has been harnessed to identify very quickly any anomalies in patients’ large datasets.
Taking thousands of data sets derived from electrocardiograms (ECG), R2 has been trained to look for abnormalities in heart function, allowing it to spot differences that might be overlooked during human evaluation. This enables R2 to make more accurate predictions of which patients may be at greater risk of cardiovascular diseases.
Unlike traditional cases in machine learning where large sets of data are needed, Permutable’s AI interface can learn directly from a domain expert. This is analogous to human-to-human learning.
This paves the way for other health applications, including tracking and classification of brain wave patterns (via electroencephalograms). This is a powerful breakthrough in facilitating early detection of neurological diseases, such as Parkinson’s Disease and Dementia. It also opens the way to applications in other areas, such as geological exploration, particularly seismic data.
Wilson Chan, Permutable CEO and Co-founder, said, “Medical application are an exciting opportunity for our proprietary R2 machine learning engine. The application of our pioneering AI technology to early detection and prevention represents a take-off point in relation to using machine learning in the medical field, particularly in areas where early detection is critical to mitigation and possibly prevention.”