The purpose of the XAI-Healthcare event is to provide a place for intensive discussion on all aspects of XAI in the medical and healthcare field. This should result in cross-fertilization among research on Machine Learning, Decision Support Systems, Natural Language, Human-Computer Interaction, and Healthcare sciences. This meeting will also provide attendees with an opportunity to learn more on the progress of XAI in healthcare and to share their own perspectives. The panel discussion will provide participants with the insights on current developments and challenges from the researchers working in this fast-developing field.

Topics:
We expect the contributions received to describe explanation methods, AI techniques and a targeted healthcare problem. Some examples are provided below for guidance, but the list of topics is not limited to these specific methods, techniques and problems.

- Model agnostic methods
- Feature analysis
- Visualization approaches
- Example-based explanations
- Fairness, accountability and trust
- Evaluating XAI
- Fairness and bias auditing
- Blackbox ML approaches: Deep learning, random forest, etc.
- Interpretable ML models: Rules, trees, Bayesian networks, etc.
- Abductive reasoning
- Counterfactual explanations
- Statistical methods
- Case-based reasoning
- Natural language processing and generation
- Infection challenges (COVID-19, antibiotic resistance, etc.)
- Chronic diseases
- Ageing & home care
- Diagnostic systems

Youtube channel:
https://www.youtube.com/channel/UCBKq6PEx2CUde1ou4TtRnkA


Workshop Proceedings:

We are aiming at providing Springer volume post-proceedings, gathering all papers presented at the workshop. Furthermore, we are also considering a proposal of a special issue of a journal like Journal of Healthcare Informatics Research (JHIR) or a similar specialized journal.