Development and Implementation of Software for Classification of brain tumours Using real-time methylation Sequencing (DISCUS)
Ultra-fast diagnosis of brain cancer during surgery with DNA analysis and AI
Our consortium will develop a software package that contains a novel AI model which uses DNA analysis to determine which type of brain cancer a patient has. The software will lead to major improvement in the treatment of brain cancer in both adults and children.
In the EU and US there are >200,000 brain tumor surgeries performed annually, which costs tens of thousands of Euros per surgery. Brain tumour classification during surgery is essential to ensure that every patient receives the optimal surgical procedure, i.e. maximising resection while minimising damage. This prevents the need for a second surgery, as well as debilitating side effects.
We have developed AI-technology for ultra-rapid classification of brain tumors based on so-called DNA methylation marks. In this project, we will drastically improve this technology to ensure optimal classification of rare tumor types and samples with low purity according to the latest classification guidelines. We will apply novel AI techniques for faster training and model calibration and develop a software user interface that enables routine application in a clinical setting. This has an immediate impact on the quality of life of patients with brain tumours as well as reducing the burden on our healthcare system.
Overall, the project will result in (i) an optimal AI model for brain tumor classification, with possibilities to use the same architecture for other tumor types, (ii) a software user interface that hosts the model and can be used for clinical reporting, and (iii) a first step towards evaluation of the software and AI model during brain tumor surgery.
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