Call for papers IEEE J-BHI special issue: Trustworthy and Collaborative AI for Personalised Healthcare Through Edge-of-Things

we are recently organising a special issue on Trustworthy and
Collaborative AI for Personalised Healthcare Through Edge-of-Things in
IEEE Journal of Biomedical and Health Informatics (J-BHI) (Impact
Factor: 7.021).

We kindly invite you and your colleagues who are interested to
contribute an article. The special issue will highlight, but not be
limited to the following topics:
*Trustworthy AI models for health, medicine, biology, and biomedical
applications
*AI-driven Edge of Things infrastructure for healthcare
*Discussion of the trade-off between explainability and performance of
machine learning
*Development of model-specific or model-agnostic approaches for
explaining machine learning models
*Generation and detection of adversarial attacks for safety in AI
systems for personalised healthcare
*Federated Learning for data privacy in AI systems for personalised
healthcare
*Fairness and bias issues in AI systems for personalised healthcare
*Designing integrating virtual agents for healthcare usages
*Collaborative robots for healthcare usages

More details can be found in the following link:

https://www.embs.org/jbhi/special-issues-page/trustworthy-and-collaborative-ai-for-personalised-healthcare-through-edge-of-things/

Thanks you and best regards,

Zhao Ren

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