CAIMed presents

CAIMed Retreat in July 2025

10:30 02-07-2025 - 16:00 03-07-2025 @ re.vita - naturresort & spa

CAIMed Retreat - July 2 to July 3

The CAIMed Retreat for all project members will take place from Wednesday, July 2, 2025, 10:30 a.m. to Thursday, July 3, 2025, 4:00 p.m
It offers space for exchange, networking, and collaborative work on the goals of CAIMed.

All groups have received funding from the CAIMed project to support participation in the retreat.
Therefore, the event involves a cost, which will be covered by each group's allocated budget.

Please fill out the online registration by April 23, 2025.

We are looking forward to your participation and to an inspiring retreat!


Important Information

📝 Binding Registration with Costs
This is a binding registration involving costs. By registering, you confirm that the expenses will be covered by your research group's CAIMed budget.

👥 Group Affiliation
Please indicate your CAIMed group affiliation in the registration form.
The group list for the participants announced so far can be found in the attachment.

📅 Partial Attendance
If you are only attending on one day, please indicate this in the registration form by checking the appropriate box.

📸 Photography
Photos will be taken during the retreat. If you do not consent to the publication of any image material, please inform the organizers in advance via email at info@caimed.de.


Ticket(s)

Free Ticket

Choose the number of tickets and click "register".
CAIMed

CAIMed is the Lower Saxony research center for artificial intelligence and causal methods in medicine. We develop innovative methods for improved, personalized healthcare and contribute to the management of widespread diseases such as cancer, cardiovascular diseases and infections. The combination of excellent locations in Lower Saxony for methodical AI research, data-intensive medicine, medical informatics and basic medical research creates a unique flagship project for research into AI and personalized medicine.

CAIMed relies on the linking of research data, clinical data and patient care data as well as the use of artificial intelligence and causal methods. This enables prevention, diagnostics, therapy and monitoring of therapeutic success to become more effective and efficient and the individual needs of each person to be better identified and served.

Contact CAIMed