Large amounts of data about this disease have already been collected by the research group of Umeå University, who tried to understand the origin of gliomas. Nevertheless, traditional statistical analyses only marginally improved the detection of gliomas. This is largely due to having only a small number of datapoints with predictive value. Detecting gliomas can thus be compared with identifying the proverbial ‘needle in the haystack’.

Heights has already developed several AI anomaly detection models (which identify ‘needles in a haystack’), for instance when building money laundering detection algorithms for the financial industry. This technical experience will now be leveraged to build the AI models which improve the early detection of gliomas.

“At Umeå University, we have a history of translating innovations into clinical applications. The Nobel Prize winning CRISPR/CAS method was discovered here and is now in clinical trials at our University Hospital,” says Beatrice Melin, Professor of Oncology at Umeå University. “I am happy about developing this new collaboration with the private sector. I profoundly believe that stimulating innovations among different fields will speed discovery of novel methods for brain tumor detection.”

More information about this project can be found on the page of Umeå University.