Abstracts. They were also a part of the overall FEMaLe project output. In the ...
About FEMaLe
Finding Endometriosis using Machine Learning is a Horizon2020 project with focus entirely on improving diagnosis, prevention and care in endometriosis. The FEMaLe project will build bridges across disciplines and sectors to translate genetic and epidemiological knowledge into clinical tools that support decision-making in terms of diagnosis and care aimed at both general practice and highly specialized endometriosis clinics – all via machine learning and artificial intelligence.
Project’s goals
Awareness
Increasing education and disease awareness for patients, public & healthcare providers will increase timely & accurate diagnosis and treatment, and allow for new advancements.
Research
The research activities such as data collecting & analysis and identifying patterns and models within FEMaLE will have in view the scientific utility and value.
Innovation
FEMaLe will create opportunities for further improvement of outcomes by developing predictive biomarkers of risk, prognosis and treatment response.
Resources
One of the main FEMaLe project’s goals is to generate knowledge.
The publications created by the project’s researchers will be published here soon.
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Popularised Outputs
With the assistance of our trusty advisers, our growing presence online and our relentless ...
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Outputs
FEMaLe project has generated outputs in relevant arenas, as seen below, to disseminate far ...
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Let’s try again
A year later Ulrik once again goes to the Danish Parliament. What has happened ...
Female project news
Thank you. You helped make life better
FEMaLe project has now entered the last five months where we will be posting ...