Towards Responsible Explainable AI in Healthcare

You are invited to join us for our online Lunch & Learn Lecture. Are you a teacher, researcher, student or in any other way interested in our collaboration? Every month one of our programmes organises a meeting about research and education of the EWUU alliance. The best part? You can join effortlessly from the comfort of your own space – simply tune in via Teams, grab your lunch, and immerse yourself in thought-provoking discussions.

This Lunch & Learn Lecture is organised by the EWUU AI programme

Towards Responsible Explainable AI in Healthcare: Knowledge Graph Construction, ELSA-Compliant Recommendations, and Predictive Modeling

In this session, Prof. Ricardo da Silva Torres (WUR) will present recent advances in explainable AI for healthcare through three complementary strands. Methods for constructing ontology-linked knowledge graphs from biomedical literature will be shown, enabling structured representation of diseases. ELSA-compliant approaches to recommender systems that combine knowledge graphs and large language models will be introduced to ensure ethical, legal, and social accountability in decision support. Finally, deep learning and transfer learning methods for predictive modeling in clinical contexts will be discussed. Together, these perspectives will be demonstrated to offer valuable guidance for designing trustworthy AI systems in medicine.