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2024 First workshop on Explainable Artificial Intelligence for the medical domain - EXPLIMED
within the 27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2024)
19-24 OCTOBER 2024 SANTIAGO DE COMPOSTELA
https://sites.google.com/view/explimed/home-page
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AI has the potential to revolutionize medical care, but there are concerns about fairness and transparency. Explainable AI (XAI) is necessary to enhance transparency, accountability, and trustworthiness in medical AI systems. XAI provides understandable insights into AI-powered clinical decision-making, enabling healthcare professionals to trust recommendations and empowering patients to actively participate in their healthcare decisions. By addressing ethical concerns related to biased or discriminatory outcomes, XAI ensures fair and equitable healthcare practices. Finally, XAI aids in the validation process, offering insights into model predictions and facilitating the integration of AI technologies into clinical workflows.
The goal of this workshop is to explore and exhibit research, methodologies, and case studies that focus on the integration of Explainable Artificial Intelligence (XAI) in the medical domain. It will provide a platform for researchers, practitioners, and policymakers to share their insights and advancements in XAI. The purpose is to improve transparency and trust in medical AI systems. The workshop aims to highlight the importance of XAI in medical decision-making, share innovative approaches and technologies that enhance interpretability in medical AI, and discuss regulatory implications and compliance strategies for incorporating XAI in healthcare AI applications.
Possible topics related to application in the healthcare domain, include (but are not limited to):
eXplainable Artificial Intelligence
Post-hoc methods for explainability
Ante-hoc methods for explainability
Rule-based XAI systems
Uncertainty modeling
XAI methods for neuroimaging and neural signals
Case-based explanations for AI systems
Fuzzy systems for explainability
Interpreting and explaining neural networks
Model-specific vs model-agnostic methods
Transparent and explainable learning methods
Interpretable representational learning
Causal inference and explanations
Bayesian modeling for interpretability
**** IMPORTANT DATES ****
Authors and Title submission: May 1, 2024
Paper submission: May 15,2024
Notification of acceptance: July 01, 2024
Final paper submission: July 15, 2024
Early registration deadline: August 15, 2024
Workshop date: October 19-20, 2024 (TBA)
**** SUBMISSIONS ****
Please make sure that all submissions are formatted in accordance with the CEUR conference style guidelines, which require a 1-column layout. The submissions should be between 6 to 10 pages in length and written in English. The paper must be submitted in PDF format via the submission system (https://sites.google.com/view/explimed/authors-guidelines/submissions). Authors are expected to use a uniform style for their papers - the Ceurart styles. We encourage authors to include their ORCIDs in their papers. In addition, any articles that are not accepted to the main conference may still be considered for publication in the workshop's proceedings. However, these articles will be subject to positive evaluation by the workshop organizers, and page limits will not apply to them.
**** PUBLICATIONS ****
All papers submitted to EXPLIMED workshop will be reviewed by independent reviewers, and upon acceptance will be submitted to CEUR Workshop Proceedings for publication, under a CC-BY 4.0 license (http://ceur-ws.org/). This means that proceedings will be free of charge, as well as of author publication charges, will be open-access, and copyright will be retained by authors. CEUR-WS proceedings are usually indexed in Scopus.
Post-workshop special issue in a well-reputed journal (details TBA) inviting extensions of accepted papers will be announced.
**** REGISTRATION ****
To attend the workshop, it is required to register for the pre-conference program and pay the registration fee, to be included in the workshop's proceedings
**** INVITED SPEAKER****
TBA
**** ORGANIZING COMMITTEE ****
Gabriella Casalino, University of Bari, Italy
Giovanna Castellano, University of Bari, Italy
Gianluca Zaza, University of Bari, Italy
**** PROGRAM COMMITTEE ****
Uzay Kaymak (Eindhoven University of Technology, Netherlands)
Corrado Mencar (University of Bari Aldo Moro, Italy)
Daniel Furtado Leite (Paderborn University, Germany)
Agnieszka Jastrzebska (Warsaw University of Technology, Poland)
Daniel Peralta (University of Ghent, Belgium)
Antonio Calcagnì (University of Padua, Italy)
Paulo Viktor Campos Sousa (Fondazione Bruno Kessler, Italy)
Katarzyna Kaczmarek-Majer (Polish Academy of Sciences, Poland)
Gennaro Vessio (University of Bari Aldo Moro, Italy)
Ben Souissi Souhir (Bern University of Applied Sciences, Germany)
TBA
**** CONTACTS ****
Any inquiries can be directed to gianlu...@uniba.it