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Groundbreaking joint statement issued on the development and use of AI tools in radiology - Vimarsana News

Groundbreaking joint statement issued on the development and use of AI tools in radiology

The American College of Radiology, working in close collaboration with four other radiology societies from around the world, have issued a joint statement on the development and use of artificial intelligence (AI) tools in radiology.

Is Adding an AI Readout to Mammography Worth It? - Vimarsana News

Is Adding an AI Readout to Mammography Worth It?

Women would have to pay out-of-pocket, as reimbursement is a long way off

Enterprise Knowledge: A Unifying Technological Vision for the Future of Radiology - Vimarsana News

Enterprise Knowledge: A Unifying Technological Vision for the Future of Radiology

Laying AI functions on top of already outdated systems or relying on separate solutions that do not play into the unified stack system––especially given the volume of data, delicate privacy issues and the need for constant updates––does not optimally contribute to the advancement of radiology.

Daily briefing: Severe COVID linked to bad fungal microbiome - Vimarsana News

Daily briefing: Severe COVID linked to bad fungal microbiome

An imbalance of fungi in the gut could contribute to excessive inflammation in people with severe COVID-19. Plus, mummified mice reveal mammals’ unexpected survival skills and the Moon could be 40 million years older than we thought. An imbalance of fungi in the gut could contribute to excessive inflammation in people with severe COVID-19. Plus, mummified mice reveal mammals’ unexpected survival skills and the Moon could be 40 million years older than we thought.

Source: nature.com
An AI revolution is brewing in medicine. What will it look like? - Vimarsana News

An AI revolution is brewing in medicine. What will it look like?

Emerging generalist models could overcome some limitations of first-generation machine-learning tools for clinical use. Emerging generalist models could overcome some limitations of first-generation machine-learning tools for clinical use.

Source: nature.com