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Artificial Intelligence


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VisionAIres: The AI data challenges in health care

VisionAIres: The AI data challenges in health care

  • Written by Chuck Martin / IoT World Today
  • 15th March 2022

The major issues around artificial intelligence in health care come down to less about the amount of data and more about data sharing, quality and reliability.

Those were the key issues members of the VisionAIres community shared in the monthly roundtable discussion comprising AI business leaders from industries including finance, media, technology, government, health care, automotive, energy, utility and transportation.

“The quantity of data isn’t the problem,” said Andrew Davies, digital health lead at the Association of British HealthTech Industries, a trade association for health technology companies. “The bigger problem is getting hold of well-organized, well-curated data.”

“We’re in the early days of using AI, but it’s starting to become more widespread, particularly considering diagnostics, where we do have more things like digital stethoscopes and the use of AI diagnosing cancer and imaging.”

The most discussed issue centered around the sharing of data, not always an easy feat.

“I’m pretty excited to see data sharing back on the roadmap for a lot of big companies, particularly with regard to AI development undertakings,” said Jutta Williams, head of privacy at Bolt and former product lead for ML, ethics transparency and accountability at Twitter.

“I’ve never found it a problem sharing information with commercial providers when there’s a well-articulated patient need demonstrated,” said Simon Mortimore, assistant director for business information at South Central Ambulance Service NHS Foundation Trust.

“My frustration with a lot of commercial providers is they don’t really know what they’re doing. They kind of want the data to play with. And we we’ve got 11 projects I’m trying to roll out and I can’t get a single commercial supplier to engage because they don’t want to play (since) we’ve actually got an outcome we’ve proven to them.”

Challenges With Data-Sharing

Data-sharing is also not always smooth sailing, several members noted.

“Where we have a serious problem is when it gets out to certain types of organizations who desperately want our data,” said Richard Self, senior lecturer in governance of advanced and emerging technologies at the University of Derby. “They can use that to assess risk for things like insurance.”

Discussion participants were aware of some of the inherent risks with data-sharing as well.

“We are just very, very careful with work on anonymization,” said Bob Compton, IS director at RCI Financial Services. “Around what we’re using, we can’t share freely at all. We’re part of the car manufacturer group, but we have to have company sharing agreements in place. There’s a lot of compliance and regulatory issues around it.”

To read the complete article, visit IoT World Today.

 

Tags: Analytics Applications Artificial Intelligence Companies Incident Command/Situational Awareness Internet of Things Internet of Things IoT/Smart X Software Tracking, Monitoring & Control Partner content

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