Biokeralty Joins TUAI Spring School to Advance Trustworthy and Explainable AI

Biokeralty Joins TUAI Spring School to Advance Trustworthy and Explainable AI

Jul 6, 2026.

Biokeralty, leader of Work Package 5 (Communication, Dissemination and Exploitation) in the OPADE project, recently participated in the TUAI Spring School, an international training event dedicated to advancing transparent, trustworthy and sustainable Artificial Intelligence (AI).

The Spring School was organised by the European doctoral network TUAI (Towards an Understanding of Artificial Intelligence via a Transparent, Open and Explainable Perspective), funded through the EU’s Marie Skłodowska-Curie Actions (MSCA). The project aims to develop a training programme to educate doctoral candidates on machine learning, its latest advancements, and how to leverage technological improvements for the benefit of European producers, while promoting transparent, open and explainable Artificial Intelligence.

During the event, participants explored cutting-edge research in key areas including time-series analysis, sensor fusion, federated learning and trustworthy AI. As a consortium partner in TUAI, Biokeralty contributes its expertise to fostering responsible AI innovation while strengthening collaboration between European research initiatives.

Building Synergies Between European Projects

Biokeralty’s participation highlights the strong scientific and technological synergies between TUAI and OPADE, where Explainable Artificial Intelligence (XAI) plays a central role in the development of predictive tools for personalised treatment of Major Depressive Disorder (MDD).

Within OPADE, AI is used to analyse complex multi-omics data and support clinical decision-making. To ensure that these predictive models are transparent and interpretable, the project incorporates state-of-the-art XAI techniques such as SHAP and Anchors. These methods help explain how the models generate predictions, transforming complex computational outputs into clear, clinically meaningful rules that healthcare professionals can understand and trust.

By making AI more transparent, OPADE aims to overcome the “black box” challenge often associated with machine learning in healthcare, fostering confidence among clinicians, regulators and other stakeholders while supporting the safe adoption of AI-driven precision medicine.

Strengthening Europe’s Responsible AI Ecosystem

Participation in events such as the TUAI Spring School reinforces OPADE’s commitment to knowledge exchange and collaboration across the European research landscape. It also supports the project’s broader objective of developing ethical, trustworthy and human-centred AI solutions that can improve healthcare outcomes for patients across Europe.