Last week, members of our research group had the privilege to participate in the 28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2025), held from 23–27 September 2025 in Daejeon, South Korea.
MICCAI is recognized as one of the most prestigious international congresses in medical image computing and computer-assisted intervention, bringing together leading researchers, clinicians, and industry professionals to share advances and foster new collaborations.
Our team presented the paper:
“Towards Breast Cancer Recurrence Prediction Using Transformer-Based Learning from Global–Local Radiomics and Clinical Data.”
This research explores how the integration of global and local radiomic features with clinical variables, modeled through Transformer-based architectures, can enhance the prediction of breast cancer recurrence. By combining complementary imaging features with clinical context, the study aims to contribute to more reliable and clinically meaningful predictive tools in oncology.
👥 Participants
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Prof. Dr. Domenec Puig — Head of the research group
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Dr. Hatem Rashwan — Associate Professor
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PhD student Adnan Khalid — Doctoral researcher
✨ Key Takeaways
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Constructive feedback on the harmonization of radiomic features across multi-center datasets.
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Stimulating discussions on the role of Transformers in unifying imaging and clinical data.
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New international collaborations initiated with research groups in medical imaging and AI for healthcare.
🚀 Next Steps
The team will continue this line of research by conducting external validation experiments and integrating interpretability and calibration analyses, aiming to bridge the gap between technical performance and clinical adoption.
Participating in MICCAI 2025 has been an enriching experience that allowed us not only to showcase our work but also to engage with the global research community driving the future of artificial intelligence in healthcare.