Ai

1. Artificial Intelligence
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STAT with no participation from sponsors.
in Health Care

5. Investment in AI health startups

7. ● mainly used in the back
● Clinical use is increasing
● Drug makers are using AI

8. ● Financial costs:
● Privacy and ethical costs:
● Reputational costs:

9. ● Imaging, imaging, imaging:
● A recent example:
● The benefit:

10. ● pump the breaks
● AI might play a role in quality
assurance and help surface research
●

12. ● AI comes in many forms
● Two main tasks:
● A third use:

13. Machine learning:
Deep learning:
Neural network:
Natural language processing:

15. ●
schedule its operating rooms
● detect the onset
of sepsis
●
target interventions to particular
patients

16. ● improving the R&D
process
●
examine the mechanisms of
disease
●

17. ●
helping with recruiting
processing and cleaning of data
● incorporate real-world evidence
● significant roadblocks to overcome

18. ● The goal:
●
● The possibilities are enormous,

20. ●
unrealistic expectations
●
skepticism and
anxiety
● slower adoption

21. ●
built in incentives to aggressively market
the use of AI
● sell their products
●
work is cutting-edge to attract patients
●
co-branding arrangements

22. ●
● needs to be grounded in facts
● dispel hype,
not peddle it.

23. The Gartner Hype Cycle
Source: www.gartner.com

24. POLL QUESTION

25. ● two extremes
● replacing doctors
curing terminal disease
● the truth
becomes much harder to suss out

26. ● AI is designed to augment
human capabilities
● doctors can focus on tasks that
matter
● Human oversight will continue to be needed

27. ● Progress is slow and incremental.
● Use in clinical practice remains largely
experimental.

29. ●
21st Century Cures Act
●
products can be exempt from
regulation if users can “independently review
● has not clarified what it means

30. ● left to determine on their own
● commercialization of
IBM’s leading cancer product, Watson for
Oncology,
●
required to do prospective studies

31. POLL QUESTION

33. ●
not enough to enable AI systems to
generate new insights
● A greater diversity of data is needed.

34. ●
Providers use different EHR systems
● harder to link data sets
● Solving this is crucial

35. ●
not perfect
●
● data must be properly obtained

36. ● hype is a continued
threat
●
need for sound science and
prospective studies.
● meaningful partnerships
● long-term vision

38. rapid increase in AI use
reason for optimism
vigilance will be necessary
clearer picture of winners and losers