Summary
The session explores roadblocks in AI adoption within healthcare, including data silos, overprotection of data, and lack of standardization. Participants emphasize the need to shift focus from sick care to proactive health management and discuss the importance of interoperability and data sharing for effective AI implementation.
Key Topics
5 key topics from this session at Future Health Summit (FHS). Thicker branches were mentioned more often in the talk.
Table 4: Infrastructure and Interoperability for AI Scalability (PaloAlto Networks))
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Key Takeaways
- Develop standards for non-clinical health data.
- Use AI to correct data quality issues.
- Focus on proactive health management, not just sick care.
- Address data sharing and benefit sharing issues.
Data Overprotection in EU
“So how can we make sure data is confidential, data is kept appropriate, data is future proof?”
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Table 11. Governance, Regulations & Responsible AI (Care Safety Innovations)
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Table 5: Infrastructure and Interoperability for AI Scalability (PaloAlto Networks)
ai in healthcareinteroperability
1:01:48
Also on interoperability
Table 6: Infrastructure and Interoperability for AI Scalability (PaloAlto Networks)
ai in healthcareinteroperability