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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“Dr. AI” will never replace a single human physician. But its many makers’ relentless pursuit of perfect performance all but guarantees the technology a prominent role in healthcare.
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This task could potentially be performed by a member of the radiology scheduling team with oversight by a clinical nurse navigator.

Partho Sengupta, MD, DM, FACC, FASE, Henry Rutgers Professor of Cardiology and Chief of Cardiovascular Medicine, at Robert Wood Johnson Medical School, and Chief of the Cardiovascular Service Line at Robert Wood Johnson University Hospital, offers an overview of the current state of artificial intelligence (AI) in cardiology. He offers insights from what he has seen from some of the more than 160 FDA-cleared algorithms specific to cardiovascular medicine and what is in development.

Exploring the evolution of AI in cardiology

Partho Sengupta, MD, shared his perspective on the current state of artificial intelligence in cardiology. The technology continues to evolve, he said, though it does still face certain limitations.

Is AI just what the doctor ordered for the radiologist shortage? Yes and no

AI shines in radiology when tasked with interpreting images of patients whose odds of illness are either very high or very low. In these cases, the technology could help mitigate burnout and supplement staffing.

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Advanced AI can provide real-time feedback to cardiologists, helping them deliver high-quality care.

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These moves come as healthcare organizations are increasingly seeking ways to integrate artificial intelligence into daily clinical duties.

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Congress should relax budget neutrality to pay for imaging AI, industry lobbying group urges

"As the nation’s largest payer of healthcare, Medicare’s policies on coverage and payment for AI technologies are especially critical," AdvaMed says.

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Deep learning reconstruction enables 5-minute MRI scans

New research in the American Journal of Roentgenology details a deep learning super-resolution image reconstruction technique that opens the door for accelerated imaging of the knee.

Artificial Intelligence

AI, politics and rising demand for imaging—how rad techs are faring amid an evolving professional landscape

Newswatch: FDA’s AI plan ‘ahead of schedule and under budget,’ AI fears vs. comforts, AI ROI, more

5 attributes every AI system will soon need to make hay in healthcare

AMA brainstorms on key topics impacting healthcare

ChatGPT excels at assessing breast pain symptoms, deciding if patients require imaging