Artificial Intelligence Computers that think? Artificial Intelligence Computers that think?
Artificial Intelligence in Health Care - Stat€¦ · Artificial Intelligence The editorial content...
Transcript of Artificial Intelligence in Health Care - Stat€¦ · Artificial Intelligence The editorial content...
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Artificial Intelligence
The editorial content in this presentation was written and produced by STAT with no participation from sponsors.
in Health Care
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Investment in AI health startups
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● mainly used in the back
● Clinical use is increasing
● Drug makers are using AI
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● Financial costs:
● Privacy and ethical costs:
● Reputational costs:
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● Imaging, imaging, imaging:
● A recent example:
● The benefit:
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● pump the breaks
● AI might play a role in quality assurance and help surface research
●
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● AI comes in many forms
● Two main tasks:
● A third use:
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Machine learning:
Deep learning:
Neural network:
Natural language processing:
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●schedule its operating rooms
● detect the onset of sepsis
●
target interventions to particular patients
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● improving the R&D process
●examine the mechanisms of
disease
●
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● helping with recruiting
processing and cleaning of data
● incorporate real-world evidence
● significant roadblocks to overcome
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● The goal:
●
● The possibilities are enormous,
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●unrealistic expectations
●skepticism and
anxiety
● slower adoption
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●built in incentives to aggressively market
the use of AI
● sell their products
●work is cutting-edge to attract patients
●co-branding arrangements
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●
● needs to be grounded in facts
● dispel hype, not peddle it.
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The Gartner Hype Cycle
Source: www.gartner.com
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POLL QUESTION
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● two extremes
● replacing doctorscuring terminal disease
● the truth becomes much harder to suss out
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● AI is designed to augment human capabilities
● doctors can focus on tasks that matter
● Human oversight will continue to be needed
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● Progress is slow and incremental.
● Use in clinical practice remains largely experimental.
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●
21st Century Cures Act
●products can be exempt from
regulation if users can “independently review
● has not clarified what it means
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● left to determine on their own
● commercialization of IBM’s leading cancer product, Watson for Oncology,
●required to do prospective studies
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POLL QUESTION
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●not enough to enable AI systems to
generate new insights
● A greater diversity of data is needed.
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● Providers use different EHR systems
● harder to link data sets
● Solving this is crucial
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●not perfect
●
● data must be properly obtained
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● hype is a continued threat
● need for sound science and
prospective studies.
● meaningful partnerships
● long-term vision
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rapid increase in AI use
reason for optimism
vigilance will be necessary
clearer picture of winners and losers
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