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Researchers from the Icahn School of Medicine at Mount Sinai have developed an AI platform that’s reportedly capable of detecting a range of neurodegenerative diseases in human brain tissue samples, according to a study published in the February issue of Laboratory Investigation.

As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms needs to undergo quality assurance (QA) reviews. How to validate radiology AI? How can you validate medical imaging AI?

Forty percent of so-called AI startups in Europe don’t actually use AI programs in their products, the Financial Times reported March 4.

Drug manufacturer Eli Lilly plans to offer a half-priced version of its insulin medication Humalog, the company announced March 4.

Using big data and AI-driven prediction models can be clinically useful, but it’s also important to learn about that data and the processes involved in collecting it, according to work published in JAMA Psychiatry.

Representatives from a handful of major global imaging societies are collaborating on a “living document” that will outline a clearer set of ethics for the use of AI in radiology.

The Blue Cross Blue Shield Association (BCBSA) published three proposals that would lower premiums by one-third for Obamacare insurance coverage and expand access to coverage for more than 4 million additional people.

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The approval, made as part of a special FDA pilot program, took just 50 days.