Programme 2022
Nordic AI Medicine and Healthcare Forum
27-28 April 2022, Stockholm

We are currently working together with our scientific advisory board to build the programme. Nordic AI Medicine and Healthcare Forum will include 40+ speakers, roundtable sessions, panel discussions, networking and more.  If you would like to be kept informed when the full programme is released pleased drop us an email:

If you have an interest in speaking please contact Steve Coldicott:

Scroll down for an example agenda.
For any enquiries about speaking opportunities or hosting a roundtable discussion please email Amanda Rafferty
Agenda Here
DAY 2 - April 28 2022
Registration, Refreshments & Networking
Welcome and Opening Remarks
Keynote Address: Developing an Optimal AI and Big Data Solution across Europe
  • Outlining the key priorities and next steps with regards to harnessing new intelligent technology for healthcare and medicine
  • Examining whether new technology solutions such as AI can be implemented within existing regulatory frameworks or what changes are required. Is it possible to find a cross-border European solution?
Marco Marsella, Head of eHealth, Well-Being and Ageing Unit - DG CONNECT, European Commission
Developing Integrated AI-Based Solutions to Optimise Data Available and Add Value in Healthcare
  • Identifying key challenges in applying Artificial Intelligence to biomedical data
  • Exploring how AI and machine learning can facilitate the collection of medical data for the objective assessment of disease progression
  • Assessing what is being done to ensure transparency and “explainability” of AI analysis to avoid prediction methods becoming a “black box” 
  • Case study: Accelerating the development and implementation of AI in healthcare
Dr Stein Olav Skrøvseth, Director, Norwegian Centre for E-Health Research
Procuring Innovation to Accelerate the Development and Implementation of AI in Healthcare
Tomas Borgegård, Innovation Program Manager, Karolinska University Hospital
Panel Q&A Discussion
Morning Refreshments & Networking
Managing the Legal, Regulatory & Ethical Implications of Using AI and Digital Technologies for Patient Data
  • Exploring the current and potential uses of AI technologies for healthcare data and the legal implications of this
  • Determining the extent to which current GDPR and other data regulations are sufficient to cover the use of data in this way: what additional data governance requirements might be needed?
  • Addressing ethical concerns with regards to patient privacy and confidentiality and ensuring any potential risks are transparent to all concerned - to what extent is anonymisation whilst allowing effective use of patient data achievable?
  • Strategies for achieving the balance between the benefits of AI techniques and maintaining regulatory compliance and patient trust & engagement
Prof Dr Ana Nordberg, Associate Senior Lecturer, Faculty of Law, Lund University
Successfully Integrating AI and Digital Healthcare into Hospitals
  • Assessing the requirements for implementing AI and digital technologies into clinics: procurement; infrastructure; stakeholder and user understanding
  • Examining how you effectively develop, validate and utilise AI decision support systems in clinical practice
  • Developing and communicating an understanding for physicians, patients and other stakeholders as to the role that AI can realistically play in health care: avoiding the risk of AI technologies becoming a “black box” 
  • Determining how healthcare institutions can implement AI and new technology solutions within highly regulated environments and severely restricted budgets
Pekka Kahri, Technology Officer, Helsinki University Hospital (HUS)
Exploring how Data-Driven Technology can be Used to Effectively Manage Healthcare Data, Break Down “Data Silos”, Increase Collaboration; and Deliver New Insights & Solutions
  • Evaluating the problems with current data sets in terms of accessibility, information gaps and format for use by all stakeholders
  • Anonymizing sensitive data and creating synthetic data to enhance data availability and sharing
  • Exploring how automation can help standardise and improve data analysis and achieve greater consistency:
    • effectively clustering data to identify variants and eliminate bias
    • making data analysis outputs reproducible 
    • improving the transparency of machine learning analysis 
  • Assessing which technologies best facilitate the flow of healthcare data
Dr Janna Saarela,  Director of the Centre for Molecular Medicine Norway (NCMM), Oslo University Hospital
Panel Q&A Discussion
Networking Lunch
Leveraging the Power of New Digital Technologies to Drive the Development of Healthcare
Healthcare provision is challenged by increasing demand and expectations to unleash the power of modern analytical tools into better outcomes for patients. Region Halland increased efficiency by transforming healthcare data to add value for patients. By means of information-driven care development it has built unique capabilities allowing for fact based systematic system-wide decision-making beyond silos, AI deployment, RWE studies and the use of novel cost allocation capabilities for complete care chains.
Dr Markus Lingman MD PhD, Chief Strategy Officer, Consultant Cardiologist, Halland Hospital Group
Applying AI and Machine Learning Approaches to Enhance Clinical Trial Success Rates
Exploring how AI tools can work alongside traditional research to identify novel targets to test in the laboratory
The Dawn of AI Digital Pathology for Cancer Diagnosis - The Karolinska University Hospital Experience
Dr Carlos Fernández Moro, Pathologist, Department of Clinical Pathology and Cytology, Karolinska University Laboratory
Panel Q&A Discussion
Afternoon Refreshments & Networking
Using AI to Advance Precision Medicine in Rare Diseases
Assessing the Role and Impact of AI in Accelerating New Drug Discovery & Development
  • Examining the extent to which AI and machine learning are being used currently in healthcare and early drug discovery and development
  • To what extent can the real impact of this be measured?
  • Harnessing the potential of AI to overcome traditional bottle-necks and accelerate new drug discovery and development – what are the next steps?
Using Artificial Intelligence to Analyse & Predict the Behaviour of Cancer Cells
Prof Dr Håvard E. Danielsen, Professor, Department of Informatics & Director, Institute for Cancer Genetics and Informatics, Oslo University Hospital and Principal Investigator, DoMore! Project
Panel Q&A Discussion
Closing Remarks from the Chair and Close of Conference
With Special Thanks to Our Sponsors, Exhibitors and Partners
© Precision Medicine Forum