Topics include, but are not limited to: Clinical validation and/or implementation of AI/ML in diagnostics, imaging, or therapeutics Predictive and prognostic modelling in clinical decision support AI-driven workflow optimization and patient management Development of interpretable and trustworthy AI systems for healthcare Multimodal data integration and federated learning in medicine Digital biomarkers, digital tools, and novel Internet of Things devices for remote patient monitoring Any other AI applications in clinical medicine not covered above Ethical, regulatory, and governance aspects of medical AI Evaluation metrics, benchmarking, and reproducibility in AI for medicine Use of AI in medical and/or health professional education Use of AI to facilitate biomedical or clinical research (clinical trials, etc.) Studies on patient, family, or health care provider attitudes towards AI and/or use of AI

From code to clinic: Translating AI into medical practice

7-9 May 2026

ICE Congress Centre
Kraków, Poland + online

Thursday, May 7: Research Day

The opening day of AIMed will be dedicated to research presentations and scientific exchange. The day will be divided into two half-day oral and poster sessions), offering a platform for both clinical and technical contributors to share their latest findings at the intersection of artificial intelligence and medicine.

All accepted abstracts will be published in a Book of Abstracts, produced in collaboration with BMJ Digital Health & AI.
The highest-scoring submissions (judged by the Research Review Committee) will be selected for oral presentations, while all accepted papers will be showcased as poster presentations throughout the conference. The top-ranked abstract will receive an invitation to submit a full paper to a Special Issue of BMJ Digital Health & AI. Invited manuscripts will undergo the journal’s standard peer-review process.

Call for abstracts

Get ready – submissions open soon!

Topics of interests

Topics include, but are not limited to:

Clinical validation and/or implementation of AI/ML in diagnostics, imaging, or therapeutics
Predictive and prognostic modelling in clinical decision support
AI-driven workflow optimization and patient management
Development of interpretable and trustworthy AI systems for healthcare
Multimodal data integration and federated learning in medicine
Digital biomarkers, digital tools, and novel Internet of Things devices for remote patient monitoring
Any other AI applications in clinical medicine not covered above
Ethical, regulatory, and governance aspects of medical AI
Evaluation metrics, benchmarking, and reproducibility in AI for medicine
Use of AI in medical and/or health professional education
Use of AI to facilitate biomedical or clinical research (clinical trials, etc.)
Studies on patient, family, or health care provider attitudes towards AI and/or use of AI

Oral presentations

Session 1A

Clinical AI will focus on original research addressing the preclinical or clinical translation of artificial intelligence and machine learning applications in medicine. Submissions should emphasize real-world implementation, validation, and clinical outcomes.

The first and presenting author in this session should be a health care practitioner.

Session 1B

AI for Medicine will highlight original research on the development of AI/ML algorithms and methods with potential clinical applications. This session will focus on model development, data science innovations, and computational methodologies.

The first and presenting author in this session should be a non-clinical researcher, such as a computer scientist, data scientist, or engineer.

Friday, May 8: State-of-the Art Day

The second day of AIMed will feature keynote and invited talks by leading experts in artificial intelligence and clinical medicine. While following a similar structure to the first day, the focus will shift from research presentations to high-level discussions on advances, challenges, and future directions in AI for healthcare.

The Plenary Day will provide an opportunity for attendees to engage directly with thought leaders from academia, healthcare institutions, and industry, encouraging critical reflection on both the promise and the practical realities of implementing AI in medicine.

Session 2A: Rebooting EBM: Path Towards EB-AIM (Evidence Based Artificial Intelligence Medicine)

Clinical AI in Practice will highlight the current state of the art in clinical applications of AI, examining how intelligent systems are being integrated into patient care, diagnostics, and hospital operations. Discussions will cover real-world deployment, clinical adoption trends, regulatory and policy frameworks, and the patient perspective on the use of AI in healthcare. Speakers will include clinicians, healthcare administrators, regulators, and representatives from patient organizations, offering a balanced and multidisciplinary view of how AI is transforming medicine today.

Marta Kwiatkowska (UK)
Opening talk: To be announced

Nadeem Sarwar (UK)
To be announced

Holger J. Schünemann (Italy)
From hype to health: Methodological framework for trustworthy AI in clinical guideline development

Artur Nowak (Poland)
Engineering the next generation of EBM tools: Using LLMs to augment expert analysis and empower patient participation

Bright Huo (Canada)
Evaluating health advice from generative AI: How do I do it, and what is the current landscape

Dan Perri (Canada)
Closing the proof-of-concept-to-production gap: AI strategy and evidence are essential in the ICU

Piotr Szymański (Poland)
AI in cardiology: From innovation to implementation

Julian Dobranowski (Canada)
AI in radiology: Challenges and opportunities. We are still here.

Sameer Shaikh (Canada)
From classroom to clinic: Building the competency framework for an AI-enabled medical workforce

Session 2B: High Tech: Emerging Frontiers in Artificial Intelligence for Medicine

Advances in AI will showcase the latest technical breakthroughs and emerging frontiers in artificial intelligence. Talks will explore topics such as foundation models, multimodal learning, generative AI, explainability, robustness, and scalability. Speakers, world-renowned AI scientists and innovators, will review key methodological advances and discuss the ongoing challenges facing AI, including data limitations, generalizability, and ethical considerations.

Piotr Sankowski (Poland)
To be announced

Marias Kostas (Greece)
To be announced

Andreas Maier (Germany)
What next in medical AI?

Petra Ritter (Germany)
AI testing and experimentation facility for health AI and robotics (TEF-Health)

Gary Collins (UK)
Inside black box: Transparent reporting for AI for healthcare

Kate Witkowski (UK)
To be announced

Session 2C: Getting Human: Strategies for Building Trust and Understanding in AI Medicine

Opening talk: Emer Cooke (Director, European Medicines Agency)
To be announced

Karl Broich (Germany)
To be announced

Ricardo Baptista Leite (Switzerland)
HEALTH AI: The GlobalAgency for Responsible AI in Health

Angeliki Kerasidou (UK)
AI, trust and future provision of health care

Rebecca Brendel (USA)
To be announced

Saturday, May 9: Innovation & Education Day

The final day of AIMed will be dedicated to hands-on learning, collaboration, and innovation. Building on the insights of the previous days, Day 3 will offer an interactive environment where participants can deepen their technical understanding, explore clinical applications in practice, and engage with cutting-edge technologies shaping the future of healthcare.

Workshops and Tutorials will provide focused, small-group sessions led by experts from academia, healthcare, and industry. These sessions will cover both foundational and advanced topics from data curation, model development, and validation, to regulatory compliance, ethical design, and clinical integration of AI tools. Tutorials will be designed to help clinicians understand how AI systems work and how to evaluate them critically, while offering data scientists and engineers practical insight into the complexities of clinical workflows and medical data.

Innovation and Education Day will showcase emerging technologies, start-ups, and translational projects bringing AI from the lab to the clinic. Live demonstrations will feature prototypes and commercially available systems in imaging, diagnostics, remote monitoring, and digital therapeutics. The Innovation and Education Day will also include panel discussions and networking sessions focused on entrepreneurship, regulatory strategy, and public–private collaboration in AI-driven healthcare.

By combining practical workshops, technical tutorials, and innovation showcases, the final day of AIMed will empower participants to translate knowledge into action, equipping both clinicians and technologists with the skills and partnerships needed to advance responsible AI adoption in medicine.

Call for Workshops, Tutorials, and Special Sessions

We invite proposals for workshops, tutorials, and special sessions addressing topics at the intersection of artificial intelligence and medicine. These sessions will form an integral part of the conference’s Innovation and Education Day on 9th May 2026.

Submission details will be announced soon.

Workshops

Proposals are also invited for focused workshops exploring specific aspects of AI in medicine such as clinical translation, regulatory frameworks, ethical design, data governance, explainable AI, or domain-specific innovations (e.g., imaging, cardiology, oncology, or digital health systems).
Workshops may combine invited talks, panel discussions, and short paper presentations. Accepted workshops will appear in the official program and may be considered for inclusion in the BMJ Digital Health & AI Book of Abstracts (subject to agreement).

Sessions

Proposals are also invited for special sessions exploring specific aspects of AI in medicine such as clinical translation, regulatory frameworks, ethical design, data governance, explainable AI, or domain-specific innovations (e.g., imaging, cardiology, oncology, or digital health systems).
Accepted sessions will appear in the official program and may be considered for inclusion in the BMJ Digital Health & AI Book of Abstracts (subject to agreement).

Tutorials

We welcome proposals for tutorials that cover core machine learning topics or emerging areas of significance relevant to both the machine learning and medical AI communities.

Tutorials should be self-contained, offering necessary background and context while engaging participants with the latest research developments, open challenges, and practical applications. Each tutorial should aim to educate rather than promote, providing a balanced overview of the field rather than focusing narrowly on the presenters’ own work or institutional projects. Tutorial proposals from academic and research institutions are strongly encouraged. Submissions with a clear commercial or marketing focus will not be accepted. Each tutorial may run for a maximum of 3 hours, including Q&A. Up to ten tutorials will be selected, scheduled across two sessions (morning and afternoon). Tutorials will be conducted on-site at the conference venue. For each accepted tutorial, presenters will receive two complimentary conference registrations.

Check the program from 2025

From data to bedside: Using big data to develop AI tools for medicine

Chairs: Prof. Bartłomiej W. Papież (UK), Prof. Dan Perri (Canada)

Introduction
Prof. Bartłomiej W. Papież (Big Data Institute, University of Oxford, UK)

Will the European Health Data Space (EHDS) contribute to the AI revolution?
Dr. Andrzej Ryś (former Director for Health Systems, Medical Products and Innovation, DG SANTE, European Commission, Belgium; EHDS Co-creator)

Clinical AI: Curiosity, or cure?
Dr. Mikael Brudfors (Senior Solution Architect, NVIDIA, UK)

AI to reduce bureaucracy in medicine
Tomasz Kopacz (Healthcare Technology Strategist at Microsoft, Poland)

AI in cardiothoracic imaging: Ready for clinical implementation?
Prof. Rozemarijn Vliegenthart (University Medical Center Groningen, the Netherlands)

Pig in a poke? Unpacking the promise and pitfalls of foundation models in health care
Prof. Bartłomiej W. Papież (Big Data Institute, University of Oxford, UK)

From concept to clinic: Bridging the healthcare AI innovation gap – observations from the OxCAIR Research group
Prof. Alex Novak (Oxford Clinical Artificial Intelligence Research, Oxford University Hospitals NHS Foundation Trust, UK)

Questions & Answers

Humans and AI view on healthcare: For users of AI tools

Chairs: Prof. Bartłomiej W. Papież (UK), Prof. Dan Perri (Canada)

Regulatory ecosystem for the AI-enabled medical devices: A brief summary for clinicians
Prof. Piotr Szymański (Chairman, Regulatory Affairs Committee of the European Society of Cardiology, National Medical Institute of the Ministry of the Interior and Administration, Poland)

Primum non nocere, secundum simulare! The ethical imperative of in silico evidence in the digital era
Prof. Alejandro F. Frangi (University of Manchester, UK)

Friend or foe? Navigating human-AI interactions in clinical practice
Prof. Bartłomiej W. Papież (Big Data Institute, Oxford University, UK)

Front-line experience in evaluating and translating AI tools into hospitals
Prof. Alex Novak (Oxford Clinical Artificial Intelligence Research, Oxford University Hospitals NHS Foundation Trust, UK)

Challenges with integrating AI into clinical workflows
Prof. Dan Perri (McMaster University, Canada)

Integration of AI in medical education
Prof. Sameer Shaikh (McMaster University, Canada)

Questions & Answers

About the conference

Artificial Intelligence in Medicine began in 2025 as a one-day meeting for health professionals and developers exploring the integration of AI into health care. It was first organized during the 10th McMaster International Review Conference in Internal Medicine (MIRCIM), an annual event held in Kraków, Poland since 2015, and more recently also online.

The initiative was developed by McMaster University’s Department of Medicine, the Polish Institute for Evidence Based Medicine (PIEBM), and Interdisciplinary Health Data Center of the Jagiellonian University Medical College.

Today, the conference has grown into a 3-day event featuring renowned international AI experts and health professionals who share real-life experience in implementing AI in different settings.

AI in Medicine started at MIRCIM 2025

Fees

Regular fee Early bird offer: €300 (standard: €400)

IN-PERSON 3 DAYS
Students & early-career researchers Early bird offer: €150 (standard: €200)

IN-PERSON 3 DAYS

What's included

Live participation in sessions and Q&A discussions
Complimentary access to live streaming
On-demand access to post-event video content
In-person networking opportunities with peers and faculty
On-site exhibits
Poster and demonstration areas
Refreshments
Conference materials (PDF)
Certificate of attendance
Satellite event: 11th McMaster International Review Conference of Internal Medicine
Satellite event: Young Talents in Internal Medicine World Finals 2026

A win-win offer with a generous return policy

Take advantage of the discounts available and register today. If later on you would like to cancel your registration, we will refund up to 100% of your payment.

Refund policy:
1 September 2025 – 31 December 2025: 100%
1 January – 31 March 2026: 50%
1 April – 6 May 2026: no refund

How does it really look?

We have selected 2 excellent lectures as a sample of what you can expect:

Prof. Alejandro F. Frangi, University of Manchester, UK: Primum non nocere, secundum simulare! Ethical imperative of in silico evidence in the digital era
Prof. Alex Novak, Oxford Clinical Artificial Intelligence Research, Oxford University Hospitals NHS Foundation Trust, UK: From concept to clinic: Bridging the healthcare AI innovation gap – observations from the OxCAIR Research group

Click the button to play the selected video.