Knowledge graphs 4 XAI in Healthcare
| Title | Knowledge graphs 4 XAI in Healthcare |
|---|---|
| Summary | Knowledge graphs in Healthcare |
| Keywords | Knowledge graphs, XAI, HealthcareProperty "Keywords" has a restricted application area and cannot be used as annotation property by a user. |
| TimeFrame | Spring 2026 |
| References | https://www.sciencedirect.com/science/article/pii/S1566253523001148
https://www.sciencedirect.com/science/article/abs/pii/S1532046425000905 https://www.sciencedirect.com/science/article/pii/S0004370221001788 https://www.sciencedirect.com/science/article/pii/S1532046423001247 https://arxiv.org/abs/2402.12608 |
| Prerequisites | |
| Author | |
| Supervisor | Grzegorz J. Nalepa, Farzaneh Etminani |
| Level | Master |
| Status | Open |
Knowledge graphs (KG) are a knowledge representation method that has became increasingly important in the context of the explainable AI approach.
Healthcare (HC) systems are a very special area of application of AI due to data sensitivity andf privacy concerns.
In this thesis we would like to conduct a survey on a recent practical applications of KG i HC for knowledge representation and management.
Furthermore, we would like to explore the role of KG in interoperability and FAIRness of HC data.
Moreover, we would like to consider KG for supporting XAI for HC, specifically what explanation forms are mostly suitable for HC experts and how they can be supported by background knowledge
Finally, we want to explore knowledge augmented retrieval with KG for HC data and knowledge bases where explanations can meet medical data.
It is encouraged that this thesis will result in scientific publications possibly also developed in collaboration with external stakeholders.
