Mark van Gils gave a presentation on AI and health, noting that health data is messy, complex and challenging due to aging populations and chronic diseases straining healthcare resources. He discussed how health data is produced throughout life, is wide-ranging, and interconnected across different databases. Van Gils proposed that AI can help address these issues through distributed computing, unobtrusive sensors providing 24/7 data, and algorithms improving from basic image analysis to integrated decision support. He concluded that while healthcare presents messy, complex challenges, AI can help fix issues by solving broader problems and enabling people to become co-producers of healthcare rather than passive objects.

1. Mark van Gils, Research Professor
AI and Health: Going
beyond Messy, Complex
and Challenging
#VTTGrowthLab

2. AI is
everywhere –
why now?
Data
Algorithms
Hardware, environment
@mark_van_gils

3. What we will
look at today
AI for Health, why is it different?
Where are we now?
What next?
@mark_van_gils

4. AIData
Algorithms need
targets
Environment
@mark_van_gils

5. AIHealthcare
specific data
Healthcare
specific targets
Healthcare environment
@mark_van_gils

6. Messy, Complex,
Challenging
• Aging population, chronic
diseases, multimorbidities
• Strain on healthcare resources
• Over 20 Billion euros in Finland,
and increasing
@mark_van_gils

7. Health Data
is long
Produced during our entire life
(epi)genetics, youth, mid-life, late-
life, post mortem
Different measures link to different
issues at different moments in life
@mark_van_gils

8. topol
March 27, 2014
Health Data
is wide
@mark_van_gils

9. Health Data is
interconnected!
Clinical database Lab database
Biobank
Research database
Monitor database
Personal devices
Helbling, Scientific American 2017@mark_van_gils

10. • Distributed
computing, AI
’everywhere’
• Unobtrusive sensors
• 365/24/7 information
Solution
Hanna Keynäs, Säde | Radiation 1-10
Piwek, PLOS Medicine 2016
@mark_van_gils

11. Algorithms
EU project PredictND, 2018@mark_van_gils

12. Speed
@EricTopol, Aug 2018@mark_van_gils

13. From image analysis to integrated views
EU projects TBIcare, CENTER-TBI@mark_van_gils

14. to full decision support
EU projects PredictAD, VPH-DARE@IT, PredictND; Combinostics Oy@mark_van_gils

15. ”AI”
Acute Care
Daily living
Sub-acute
care
Society
Scientific
Community
Finnish &
international
industry
improved
decision
making!
efficient care!
quality
of life!reduced
costs!
increased
competetiveness!
increased
knowledge!
healthcare
professionals
citizens
Finnish and global
industry and
decision makers
More
ambitious
targets for
algorithms
@mark_van_gils

16. Interventions and
smart choices
• Preventive
• Personalised
• Precise
• Pervasive
@mark_van_gils

17. after prof. Niilo Saranummi, VTT
From passive
objects to
co-producers
@mark_van_gils

18. • Data
Everyday-day, all-day, everywhere
Extremely connected, AI close to the sensors
• Algorithms
Meaningful, ambitious goals
Explainability
• Environment
Smart assistants
Process optimisation
Motivational tools
The future
@mark_van_gils

19. Concluding
Messy, complex, challenging -
but we’ll fix it
From obvious tasks to
solving the big picture
No passive objects!
@mark_van_gils

20. Thank you!
@mark_van_gils
#VTTGrowthLab