Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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artificial intelligence in healthcare

AI accurately reads brain MRIs in seconds

The tool can identify over 50 different neurological conditions with nearly 98% accuracy.

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Medicare contractor proposes denying coverage for AI-based brain MRI technology

If finalized, the decision would impact radiology providers across Illinois, Minnesota, Wisconsin, Connecticut, New York, Maine, Massachusetts, New Hampshire, Rhode Island and Vermont. 

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RadNet pays $33M to acquire cloud-based imaging solutions provider

The Los Angeles company previously announced it was acquiring Cimar UK in November, with a new SEC filing revealing further details about the purchase agreement. 

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Combining structured reporting with AI drastically reduces turnaround times

Both structured reporting and AI support have been touted as promising solutions for streamlining workflows while also making radiologists' results more consistent.

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Does Moltbook have anything to do with healthcare? Should healthcare have anything to do with Moltbook?

The self-described “social network for AI agents”—humans can observe but can’t chime in—launched one week ago. But Moltbook already has an awful lot of people fussing and fighting over what it means in the grand scheme of all things AI. 

FDA clears algorithm that detects and quantifies incidental lung nodules

FDA clears algorithm that spots and quantifies incidental lung nodules

The platform provides radiologists with a Malignancy Similarity Index score, used to help determine the likelihood that an incidental nodule is malignant.

Walter Wiggins, MD, PhD, a neuroradiologist and director of clinical AI at Mosaic, explains how large language model (LLM) artificial intelligence is increasingly being used in radiology to extract structured data from narrative radiology reports to improve workflow, and to help validate, monitor and improve other AI tools being used in clinical practice.

How Radiology Partners is using large language models to monitor AI deployment

This type of tracking helps a practice understand how radiologists interact with AI, whether they're appropriately rejecting incorrect results, and if the technology is improving detection of important findings.

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Medtronic to acquire AI-enabled FFR specialists CathWorks for up to $585M

Medtronic has held a minority investment in CathWorks for several years, and the two organizations entered into a co-promotion agreement in 2022. Once finalized, the move will increase Medtronic's presence in the cath lab. 

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