- The directors of the Foundation and the Breast Area of the health group, Mercedes Gozalbo and Julia Camps, attend the meeting of the European project that develops “swarm learning” to improve the precision of Artificial Intelligence
- The meeting, held in Athens, makes it possible to advance a common tool that will help anticipate the disease, improve individualized treatments and control its evolution more precisely, reducing the uncertainty of patients.
Artificial Intelligence is not the future, it is the present. For this reason, the Ribera health group has been part, for several months, of the work team of the European ODELIA project, whose objective is to develop an advanced Artificial Intelligence model, which includes a secure exchange of data, in this case to create predictive models. and even more personalized follow-up for breast cancer. This week, the project has taken a new step to advance a common tool, which will allow the exchange of highly valuable information without sharing patient data, with the working meeting attended by the directors of the Ribera Salud Foundation and from the Breast Area, Mercedes Gozalbo and Julia Camps respectively. “The next step is for all of us to start uploading images and data, to help the AI model learn,” explains the director of the Foundation.
The international prestige of the Breast Area of the group, led by Dr. Camps, and the large number of patients treated in the breast units of the Ribera hospitals, make Ribera a strategic partner of this European project. “ODELIA will help improve individualized treatments for patients and will also be a tool to help predict disease. In addition, it will reduce uncertainty about the evolution of breast cancer, thanks to the prediction model, as well as the response to drugs, which will allow patient treatment to be personalized earlier and with more certainty,” explains Dr. Julia Camps.
The ODELIA project is a decentralized swarm machine learning solution, which allows multiple collaborators to share information without sharing the patient data itself, protecting patient privacy and security, while still allowing all collaborators to benefit. of collective learning. Data governance and privacy are preserved.
“When organizations only have access to their own data, their AI models evolve based solely on information about the people the organization has worked or works with, creating bias in the models. With swarm learning, an organization can combine its data with the learning of other organizations, increasing precision and reducing bias,” explains the director of the Ribera Salud Foundation.
The next meeting of the ODELIA project will take place in spring.
