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. 

Rayus Radiology launches whole-body MRI service in Seattle, SimonMed expands, RadNet touts legislation, plus more company news

Also, Envision names new general counsel, RBMA recognizes imaging leaders, practice experiences data breach, an $857M merger deal Down Under and more. 

american college of radiology ai quality assurance center

ACR opens doors of AI quality-assurance center

Radiology practice leaders have a new way to assure their patients, communities, referrers and payers—and their own people—that the AI products they use are in compliance with safety and efficacy guidelines set by the American College of Radiology.

Peter Monteleone, MD, an interventional cardiologist, national director of cardiovascular research at Ascension Health, and assistant professor, UT Austin Dell School of Medicine, explained the use of artificial intelligence (AI) to independently identify an emergency stroke or pulmonary embolism (PE) finding on a CT scan and automatically alert critical care team members. His health system uses this type of AI for earlier activation of the pulmonary embolism response team (PERT).

AI critical care software revolutionizes emergency response

Ascension Health in Texas uses AI that can read CT scans for stroke and pulmonary embolism to activate care teams before the images even get into the PACS.

Strategic Radiology and Qure.ai

Strategic Radiology signs on with Qure.ai

A coalition of independent imaging practices is partnering with a radiology AI startup specialized in automated interpretation algorithms.

The ASNC team at the 2024 AMA meeting, Georgia Lawrence, JD, ASNC director of regulatory affairs; Suman Tandon, MD, FASNC, delegate to the AMA HOD and cardiac imager at NYU Langone; and Kathy Flood, ASNC CEO. #AMA #AMA24 #AMA2024 #AMAHOD #ASNC

ASNC supports AMA effort to limit use of AI in prior authorization decisions

The American Society of Nuclear Cardiology (ASNC) supports an AMA policy that condemns the use AI to make prior authorization decisions rather than a doctor or clinician.

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American College of Radiology asks CMS to create new alternative payment pathway for high-value AI

ACR’s June comments come in response to the 2025 Hospital Inpatient Prospective Payment System rule released by CMS in April. 

The rapid rise of artificial intelligence (AI) has helped cardiologists, radiologists, nurses and other healthcare providers embrace precision medicine in a way that ensures more heart patients are receiving personalized care.

ACR urges radiologists to speak up as Medicare considers covering imaging AI software

New York-based vendor Cleerly recently petitioned CMS to pay for its primary CT software, which assesses scans for signs of coronary artery disease. 

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Why practices might want to think twice before using ChatGPT to create patient education materials

"The potential for disseminating inaccurate information and the occurrence of 'hallucinations'—responses that are generated without grounding in factual data—are significant concerns,” authors of a new analysis warn.

Around the web

After reviewing years of data from its clinic, one institution discovered that issues with implant data integrity frequently put patients at risk. 

Prior to the final proposal’s release, the American College of Radiology reached out to CMS to offer its recommendations on payment rates for five out of the six the new codes.

“Before these CPT codes there was no real acknowledgment of the additional burden borne by the providers who accepted these patients."

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