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News You Need to Know Today
Enterprise Imaging: If AI is the future, move to the cloud | Sectra inks NHS partnership | Collab promotes imaging standard
Thursday, December 21, 2023
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Today's News and Trends

If AI is the future, radiology needs to look to the cloud

In a recent journal op-ed, experts compared radiology's move to cloud to the shift from film to digital.

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If AI is the future, radiology needs to look to the cloud

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In a recent journal op-ed, experts compared radiology's move to cloud to the shift from film to digital.
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Sectra inks 10-year partnership with Scotland's NHS, moving 55M radiology studies to the cloud

The National Health Service in Scotland covers 14 territories and is seeking support for its professionals with the reading, sharing, and storage of over 5 million scans annually. 

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Sectra inks 10-year partnership with Scotland's NHS, moving 55M radiology studies to the cloud

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2000px-flag_of_scotland.svg_.png
The National Health Service in Scotland covers 14 territories and is seeking support for its professionals with the reading, sharing, and storage of over 5 million scans annually. 
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Specialty hospital moves enterprise PACS to the cloud

RML Specialty Hospital serves patients in need of long-term hospital stays in the greater Chicago area.

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Specialty hospital moves enterprise PACS to the cloud

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RML Specialty Hospital serves patients in need of long-term hospital stays in the greater Chicago area.
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Collaboration brings AI-driven imaging standards to healthcare organizations

Enlitic and Infinitt North America hope their partnership will inspire new research.

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Collaboration brings AI-driven imaging standards to healthcare organizations

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Enlitic and Infinitt North America hope their partnership will inspire new research.
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AI model with single-source dataset outperforms multi-institution version

Despite the results, researchers still recommend using models trained on multi-institutional datasets.

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Damaged Organ
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AI model with single-source dataset outperforms multi-institution version

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Damaged Organ
Despite the results, researchers still recommend using models trained on multi-institutional datasets.
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