A predictive model for endometriosis
Healthcare tools for predicting and preventing diseases as well as personalising treatment and patient management offer great clinical benefits and cost reduction. The EU-funded FEMaLe project is working on a machine-learning multi-omics platform that can analyse omics data sets and feed the information into a personalised predictive model. The main focus of the project is to improve intervention for individuals with endometriosis, a condition where tissue normally lining the uterus grows outside the uterus. A combination of tools such as a mobile application and augmented reality surgery software will be developed, facilitating improved disease management and the delivery of precision medicine.
Fields of science
Call for proposal
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Funding SchemeRIA - Research and Innovation action
OX29 8LJ Witney