HC@AIXIA 2026: [CFP] HC@AIxIA 2026 (AIxIA 2026)

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🆕 DEADLINE EXTENDED 🆕 New submission deadline: August 4, 2026, Anywhere on Earth (AoE)

Submit here: https://chairingtool.com/conferences/aixia2026/main-track?role=author 🆕 DEADLINE EXTENDED 🆕

================================================================================ CALL FOR PAPERS - DEADLINE EXTENDED ================================================================================

5th International AIxIA Workshop on Artificial Intelligence for Healthcare HC@AIxIA 2026

Perugia, Italy, October 6-9, 2026 https://sites.google.com/unical.it/hcaixia2026/

Co-located with the 24th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2026) https://aixia2026.unipg.it/

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== IMPORTANT UPDATE ==

The previously separate abstract and paper submission deadlines have been merged into a single submission deadline.

Authors may register and submit their contributions until August 4, 2026, Anywhere on Earth (AoE).

== INFORMATION ==

In a rapidly evolving world where AI is increasingly embedded in critical sectors, healthcare stands out as one of the domains where Artificial Intelligence can have the greatest scientific, technological, clinical, and societal impact. AI-based solutions are increasingly affecting medical research, clinical practice, healthcare management, public health, and patient-centered care.

The HC@AIxIA workshop provides a forum for exploring the application of Artificial Intelligence to healthcare in its broadest sense. It aims to bring together researchers and practitioners from academia, industry, medical centers, public-health institutions, and related communities, fostering interdisciplinary collaboration between AI researchers, health informaticians, clinicians, biomedical researchers, healthcare professionals, and stakeholders involved in the design, deployment, evaluation, and governance of AI-based healthcare systems.

Healthcare and medicine require complex decision-making processes involving diagnosis, treatment selection, treatment planning, monitoring, prognosis, prevention, and long-term care. Addressing these challenges requires methods from the whole spectrum of AI, including machine learning, knowledge representation and reasoning, planning, natural language processing, probabilistic and causal models, optimization, human-centered AI, and decision-support systems.

At the same time, healthcare is grounded in a rich and evolving body of domain knowledge, including clinical guidelines, medical vocabularies, biomedical ontologies, temporal and spatial patterns, pathophysiological knowledge, molecular and genetic characterizations, and organizational constraints. Such knowledge can play a key role in developing AI systems that are accurate, reliable, explainable, trustworthy, clinically meaningful, and effectively usable in real-world healthcare settings.

After the 2025 joint edition with HYDRA, co-located with ECAI 2025, HC@AIxIA 2026 returns as a focused workshop of the HC@AIxIA series, co-located with the annual AIxIA conference, while preserving the interdisciplinary and methodological breadth developed in previous editions.

== CALL FOR PAPERS ==

The workshop welcomes original research contributions, summaries of recent work, and work-in-progress studies on frameworks, applications, methodologies, tools, and systems concerning the use and impact of Artificial Intelligence in healthcare.

Submissions are welcome from a wide multidisciplinary spectrum of researchers and practitioners, including computer scientists, AI researchers, health informaticians, clinicians, biomedical researchers, public-health experts, epidemiologists, healthcare professionals, medical institutions, public-health agencies, industry, startups, and other stakeholders interested in AI-based solutions for healthcare.

Collaborations across disciplines are especially encouraged, as they can help bridge the gap between AI methods and real-world healthcare needs, supporting the development of actionable, trustworthy, and clinically meaningful AI-driven solutions.

Possible topics of interest are, but are NOT limited to:

* Machine learning, data mining, and statistical methods for clinical decision support * Knowledge representation, reasoning, and formal argumentation in healthcare * Hybrid, neuro-symbolic, and knowledge-enhanced AI for healthcare * Explainable, transparent, accountable, and trustworthy AI in healthcare * Large language models, generative AI, and foundation models for healthcare * Natural language processing for clinical texts, electronic health records, and biomedical literature * Medical imaging, signal processing, and multimodal AI in healthcare * Probabilistic graphical models for clinical decision-making * Causal models, causal discovery, and causal reasoning in healthcare * Learning, representation, and reasoning with time * Methods for diagnosis, treatment selection, treatment planning, and prognosis * Monitoring patients in healthcare * Personalized medicine and patient-centered decision support * Computer-interpretable clinical guidelines and clinical pathways * Ontologies, medical vocabularies, knowledge graphs, and semantic technologies * Privacy-preserving, federated, and distributed AI for healthcare * Fairness, bias, robustness, safety, and reliability of medical AI systems * Human-centered AI, usability, clinical adoption, and interaction with healthcare professionals * AI for public health, epidemiology, surveillance, and prevention * Ethical, legal, social, and regulatory aspects of medical AI * Evaluation methodologies, benchmarks, reproducibility, and validation of AI systems in healthcare * Tools for supporting authoring, execution, and maintenance of clinical protocols and guidelines * Tools for building, deploying, and monitoring clinical decision-support systems