Machine learning (ML) and artificial intelligence (AI) are, without doubt, among the hottest topics in clinical research, topics that also interest diverse stakeholders and the general public. Despite the promise of ML/AI and the vast number of research articles about it in the medical literature (~80,000 on PubMed in 2023), implementation of AI-based solutions in clinical practice is still sparse. One of the potential reasons is the lack of a basic understanding of what problems ML can and cannot solve. This is partly due to a knowledge gap and language barrier between data science and clinical research.

This course embraces an interdisciplinary approach and introduces topics in ML/AI through examples from the clinical literature. By doing this, ML/AI can be presented to a broad scientific audience across disciplines. This is an important step towards critical thinking about ML and AI-based applications for healthcare.

Specifically, participants in this course will:

• Explain the differences between traditional statistical methods and ML
• Understand the steps of development and validation of clinical prediction models
• Critically evaluate clinical studies using ML and AI-based solutions in healthcare
• Cover fundamental concepts in ML/AI (from basic to state-of-the-art) to provide a ‘springboard’ to more complex ML/AI studies
• Unravel common misunderstandings about ML/AI
• Discuss societal considerations of AI-based solutions in healthcare

Speakers:

• Adam Hulman, Senior Researcher & Associate Professor, Steno Diabetes Center Aarhus & Department of Public Health, Aarhus University (DK)
• Benjamin Lebiecka-Johansen, Postdoctoral Researcher, Steno Diabetes Center Aarhus (DK)
• Inchuen Huynh, PhD Student, University of Copenhagen (DK)
• Simon Tilma Vistisen, Associate Professor, Department of Clinical Medicine, Aarhus University (DK)
• Veronika Cheplygina, Associate Professor, IT University of Copenhagen (DK)

Organisers:

• Adam Hulman, Senior Researcher & Associate Professor, Steno Diabetes Center Aarhus & Department of Public Health, Aarhus University (DK)
• Benjamin Lebiecka-Johansen, Postdoctoral Researcher, Steno Diabetes Center Aarhus (DK)

Assistants:

• Helene Bei Thomsen, PhD Student, Steno Diabetes Center Aarhus & Department of Public Health, Aarhus University (DK)
• Manuel Mounir Demetry Thomasen, PhD Student, Steno Diabetes Center Aarhus & Department of Public Health, Aarhus University (DK)

This course is intended for early career researchers working within any field of or related to diabetes or endocrinology. Early-career researchers include advanced MSc students, PhD students, postdoctoral researchers, clinicians aiming to start a PhD student or postdoctoral position, or similar.

The primary target group is early-career researchers with little or no experience with machine learning. Thus, we encourage those without any prior knowledge of or experience with machine learning to apply.

Participants will be selected based on a motivation statement provided via the registration form. We will select participants with a clear, relevant motivation. We also will form a diverse group, based on research area, gender, geography, etc.

Please note that you are not guaranteed a seat at the event if you do not meet the target group requirements. Priority may be given to participants employed at Danish research and health institutions or life science industry. Early-career researchers from abroad are welcome to apply. If the event is overbooked, DDEA reserves the right to select participants based on the defined requirements.

Dinner registration
DDEA organizes networking dinners on 21 and 22 January 2025. Participation in the dinners is free of charge. Please sign up for the dinners upon registration, and indicate whether you have any dietary requirements.

Accommodation
DDEA offers two nights of hotel accommodation for participants living outside of the Aarhus area. Check-in is on 21 January 2025, and check-out is on 23 January 2025.

Please sign up for accommodation when you register for the event. You will be informed about your overnight accommodation by DDEA after the registration deadline.

Certification
A course certificate will be sent to all participants upon request at the end of the course. Full participation is required to attain 1,9 ECTS points.

Latest cancellation date & no-show fee
Please note that it is free of charge to participate in the event however the DDEA will charge a no-show fee of 1000 DKK if you do not show up and have not unregistered from the event by 8 January 2025.