We presented STAGE project results on explainable AI at the EFMI Special Topic Conference 2026 in Athens

Athens, Greece, 29–31 October 2026 – SRDC presented the latest results from the STAGE project at the EFMI Special Topic Conference 2026 (EFMI-STC 2026). This year’s conference focused on AI in Clinical Decision Making and Education and coincided with the 50th anniversary of the European Federation for Medical Informatics (EFMI).

On 30 October, Bunyamin Sarigul presented the paper “From Feature Definitions to Decision Support: Deploying Explainable ML Models as Plug-and-Play FHIR Services” in Session 12: Health Informatics and AI. The paper reports results from Work Package 7 of STAGE. It shows how explainable machine learning models can be brought closer to clinical practice by deploying them as interoperable, HL7 FHIR-based decision support services.

The paper was co-authored by Bunyamin Sarigul, Tuncay Namli, Mustafa Yuksel, Zeynep Ecem Kartal and Gokce Banu Laleci Erturkmen from SRDC. Their co-authors from STAGE partner institutions were Alvaro Passi-Solar (Artificial Intelligence in Medicine Lab, Universitat de Barcelona), Michele Atzeni (Ab.Acus) and Teija Juola and Sylvain Sebert (Research Unit of Population Health, University of Oulu).

STAGE (Stay Healthy Through Ageing) is a six-year Horizon Europe project coordinated by the University of Oulu. It aims to show that a life-course approach can prevent accelerated ageing, which happens when multiple chronic conditions build up over time. The project is developing AI-powered, person-centred solutions for early diagnosis, screening, treatment and long-term management.

Acknowledgement
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No. 101137146. UK participants in STAGE are supported by UKRI grant numbers 10112787, 10099041 and 10109957.