To help create a workplace environment that’s suitable for everyone, the British Standards Institution ...
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.
FEMale Video Explainer
Latest News
Female project news
EMPLOYERS!
FEMaLe Project acknowledges and commends Endometriosis UK’s quest for more #endometriosis friendly employers. The ...
Female project news
The ripples of endometriosis
Its impact ripples. Whether it be physical, mental or less immediately obvious, make no ...
Female project news
The link between endometriosis, work & social participation
The negative effects of #endometriosis on work and social participation have been documented, emphasizing ...
Female project news
It took me 25 years to get a diagnosis.
Granted, Sara-Sofia here has waited longer than average to get her #endometriosis diagnosis, but ...