Connectionists: 1st CFP: Workshop XAI-Healthcare 2023. Slovenia, June 15, 2023

[Alfredo Vellido]

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Apologies for cross-posting

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*1-day workshop June 15, 2023*in conjunction with*AIME 2023 
*(https://aime23.aimedicine.info), Portoroz, Slovenia

https://www.um.es/medailab/events/XAI-Healthcare/*
*

*Important dates*
*April 24*, 2023 Paper submission
*May 11*, 2023 Acceptance
*May 15*, 2023 Final mansucript

The purpose of XAI-Healthcare 2023 event is to provide a place for 
intensive discussion on all aspects of eXplainable Artificial 
Intelligence (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.

Explainable AI (XAI) aims to address the problem of understanding how 
decisions are made by AI systems by designing formal methods and 
frameworks for easing their interpretation. The impact of AI in clinical 
settings and the trust placed in such systems by clinicians have been a 
growing concern related to the risk of introducing AI into the 
healthcare environment. XAI in healthcare is a multidisciplinary area 
addressing this challenge by combining AI technologies, cognitive 
modeling, healthcare science, ethical and legal issues.

*Submission Guidelines
*Submission website: 
https://easychair.org/conferences/?conf=xaihealthcare2023

All papers must be original and not simultaneously submitted to another 
journal or conference. The following paper categories are welcome:

*Explanation Approaches*:
Model agnostic methods
Feature analysis
Visualization approaches
Example and counterfactuals based explanations
Fairness, accountability and trust
Evaluating XAI
Fairness and bias auditing
Human-AI interaction
Human-Computer Interaction (HCI) for XAI
Natural Language Processing (NLP) Explainability

*AI techniques*:
Blackbox ML approaches: DL, random forest, etc.
Interpretable ML models: Rules, Trees, Bayesian networks, etc.
Statistical models and reasoning
Case-based reasoning
Natural language processing and generation
Abductive Reasoning

*Target healthcare problems*:
Infection challenges (COVID, Antibiotic Resistance, etc.)
Trustworthy AI
Chronic diseases
Ageing & home care
Diagnostic systems

*Organizing Committee*
Concha Bielza, Dept. of Artificial Intelligence, Universidad Politécnica 
de Madrid
Pedro Larrañaga, Dept. of Artificial Intelligence, Universidad 
Politécnica de Madrid
Primoz Kocbek, Faculty of Health Sciences, University of Maribor
Jose M. Juarez, Faculty of Computer Science, Universidad de Murcia
Gregor Stiglic, Faculty of Health Sciences, University of Maribor
Alfredo Vellido, Universitat Politècnica de Catalunya and IDEAI-UPC
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