The purpose of XAI-Healthcare 2022 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.

Previous editions

Invited speaker

Lisiane Pruinelli, PhD, MS, RN, FAMIA

Lisiane Pruinelli

Associate Professor in the School of Nursing

University of Minnesota.


"A Holistic View of the Drivers for Explainable AI"

+info about L. Pruinelli

Online activities & Program

This workshop is an hybrid face-to-face/online event.

Schedule XAI-Hlealthcare2022


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.

Explanation Approaches:
  • Model agnostic methods
  • Feature analysis
  • Visualization approaches
  • Example-based Explat.
  • 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, etc.
  • Statistical methods
  • Case-based reasoning
Target healthcare problems:
  • Infection challenges (COVID, Antibiotic Resistance, etc.)
  • Trustworthy AI
  • Chronic diseases
  • Ageing & home care

Important Dates

  • March 10, 2022 Paper submission (extended deadline)
  • March 15, 2022 Acceptance
  • March 30, 2022 Final mansucript
  • Jun 11-14, 2022 1-day Workshop


Papers should be submitted to the XAI-Healthcare Easy Chair Website at SUBMIT LINK . Papers should be formatted according to IEEE Proceedings Format ( FORMAT LINK).

The workshop features regular papers in a single category: short papers (up to 6 pages) describing either original research projects or work-in-progress.

All accepted papers will appear in the conference proceedings which will be published in IEEE ICHI 2022 proceedings book (IEEE Acess).

Special Issue Journal

Best papers presented will be invited to extend their manuscript for possible publication in the Special Issue on XAI at an international scientific journal.

Workshop Organisers

  • Primoz Kocbek, Faculty of Health Sciences, University of Maribor [contact]
  • Jose M. Juarez, Faculty of Computer Science, University of Murcia [contact]
  • Gregor Stiglic, Faculty of Health Sciences, University of Maribor [contact]
  • Cristopher Yang, College of Computing & Informatics, Drexel University[contact]
  • Huang Zhengxing, Faculty of Biomedical Engineering, Zhejiang University[contact]
  • Program Committee

    • Przemek Biecek, University of Wroclaw
    • Pedro Cabalar, University of Coruna
    • Bernardo Canovas-Segura, University of Murcia
    • Carlo Combi, University of Verona
    • Zhe He, Florida State University
    • Stewart Massie, Robert Gordon University
    • Martin Michalowski, University of Minnesota
    • Enea Parimbelli, University of Pavia
    • Thai-Hoang Pham, The Ohio State University
    • Alejandro Rodriguez, Technical University of Madrid
    • Supreeth Shashikumar, University of California San Diego

    Activities & Program

    XAI-Healthcare will include paper presentations and invited talks related to the workshop topics listed above. All submitted papers will be subject to a review by the workshop Program Committee. Based on the number of high-quality submissions we will define the length of the presentations that will be followed by time for questions and discussion from the audience.