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.

Cardiology ranked No. 2 among all specialties with 122 FDA-cleared AI models
Only radiology is associated with more FDA-cleared AI algorithms than cardiology, according to new federal data.
Almost 80% of knowledge workers bring their own GenAI to work
Around the world, 3 of 4 workers who routinely handle information are now using generative AI on the job. And almost half of them are new to the technology, having begun using it only over the past half-year.
So much healthcare data, so many missed opportunities
Four of five hospital leaders trust the accuracy of their institution’s data. Yet almost half of useable data gets underutilized if not completely untapped for guiding business and clinical decisions.
Biden Administration itemizes AI accomplishments to date
Half a year after President Biden officially directed federal agencies in the executive branch’s bailiwick to “seize the promise and manage the risks” of AI, the White House has posted a status report.
Large language models, other GenAI options stimulating tech purchasing in healthcare
Budgeting for generative AI in healthcare has skyrocketed, albeit in pockets, by as much as 300% year over year.

Remote ECG access on a smart phone via the Viz.ai Cardio Suite, which enables access to dynamic ECG, echo, MRI, CT images and reports. It also enables automated detection on imaging to alert care teams for STEMI, hypertrophic cardiomyopathy, pulmonary embolism, aortic dissection and abdominal aortic aneurysm, and heart failure.

Cardiology ranked No. 2 among all specialties with 122 FDA-cleared AI models

Only radiology is associated with more FDA-cleared AI algorithms than cardiology, according to new federal data.

May 14, 2024

Almost 80% of knowledge workers bring their own GenAI to work

Around the world, 3 of 4 workers who routinely handle information are now using generative AI on the job. And almost half of them are new to the technology, having begun using it only over the past half-year.

May 14, 2024

So much healthcare data, so many missed opportunities

Four of five hospital leaders trust the accuracy of their institution’s data. Yet almost half of useable data gets underutilized if not completely untapped for guiding business and clinical decisions.

May 8, 2024

Biden Administration itemizes AI accomplishments to date

Half a year after President Biden officially directed federal agencies in the executive branch’s bailiwick to “seize the promise and manage the risks” of AI, the White House has posted a status report.

May 2, 2024

Large language models, other GenAI options stimulating tech purchasing in healthcare

Budgeting for generative AI in healthcare has skyrocketed, albeit in pockets, by as much as 300% year over year.

April 30, 2024

Against malpractice for using clinical AI, the best defense is a good offense

If a clinician you care about counts on AI to help make medical decisions, remind them: Tort law principles hold that doing so means risking liability should a patient sue over harm done.

April 25, 2024

Q&A: Cleveland Clinic’s Lars Svensson previews AATS annual meeting

Svensson, a prominent voice in cardiothoracic surgery, said he has seen a rise in enthusiasm ahead of this year's meeting.

April 23, 2024

Advanced artificial intelligence (AI) models can evaluate cardiovascular risk in routine chest CT scans without contrast, according to new research published in Nature Communications.[1] In fact, the authors noted, the AI approach may be more effective at identifying issues than relying on guidance from radiologists. Representative non-contrast CT slices for two patients (left), with super-imposed segmentations (right). One artificial intelligence (AI) model was used to segment a cardiac mask.

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.

April 23, 2024

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The push for an independent cardiology board continues

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