Programme 2020
Nordic AI Medicine and Healthcare Forum
16-17 March 2020, Stockholm

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16-17 March 2020, Stockholm
DAY 2 - Tuesday 17th March 2020
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08:30
Registration, Refreshments & Networking
09:00
Welcome and Opening Remarks
09:05
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

09:35
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 development of complex, digital biomarkers and advanced diagnostics 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

10:00
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

10:25
Panel Q&A discussion
10:40
Morning Refreshments & Networking
11:10
Managing the Legal, Regulatory & Ethical Implications of Using AI for Analysing, Sharing & Manipulating Biological & Patient Data
  • Exploring the current and potential uses of AI technologies for analysing, integrating and managing healthcare data 
  • 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
12:00
Procuring Innovation to Accelerate the Development and Implementation of AI in Healthcare
  • Exploring the current and potential uses of AI technologies for analysing, integrating and managing healthcare data 
  • 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

   Tomas Borgegård, Innovation Program Manager, Karolinska University Hospital

12:30
Networking Lunch
13:30
Successfully Integrating AI into Hospitals and Clinics to Reduce Long-Term Costs and Improve Patient Outcomes
  • Assessing the requirements for implementing AI 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
14:15

Leveraging the Power of New Digital Technologies to Translate Healthcare Data into Actionable Information and Facilitate Clinical Application

  • Examining the potential of AI and machine learning to identify significant targets and design assays with less markers
  • Exploring how these new technologies can work effectively alongside traditional research and decision-tools and human insight
14:45
Afternoon Refreshments & Networking
15:10
Using AI to Advance Precision Medicine in Rare Diseases
15:35
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?
16:00
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

16:25
Closing Remarks from the Chair
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