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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FDA clears new AI algorithm for 1-year AFib risk

The new algorithm from Tempus AI evaluates 12-lead ECG results, alerting users when a patient could be at risk of experiencing AFib within the next 12 months.

AliveCor, a California-based healthcare company focused on developing on-the-go electrocardiography (ECG) devices, has gained U.S. Food and Drug Administration (FDA) clearance for its KAI 12L artificial intelligence (AI) technology and the new handheld Kardia 12L ECG System.

Dual approvals: AliveCor gains FDA clearance for advanced AI model, handheld ECG system

One of the company's new approvals was for a pocket-sized ECG system designed to be less invasive and easier to use than other devices on the market. 

artificial intelligence robot evaluates healthcare data

AI-powered platform for arrhythmia detection gains FDA approval

The newly approved DeepRhythm Platform from Medicalgorithmics uses advanced AI to evaluate imaging results and look for signs of cardiac arrhythmias.

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Heart surgeons are fed up with old technology—many have considered a career change

A majority of U.S. surgeons, including those who treat heart patients on a daily basis, say their operating rooms use outdated technology. It is having a negative impact on patient care. 

artificial intelligence in cardiology

AI can help cardiologists predict death after TAVR—but there is a catch

It's clear that advanced AI algorithms will radically transform care for TAVR patients in the years ahead. For now, however, certain AI models may require too much data to be helpful on a consistent basis. 

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.

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.

The central illustration from a study that shows the impact of ECG AI algorithm study case and control selection to train artificial intelligence to better screening patients for cardiac amyloidosis. Image courtesy of JACC Advances.

Using ECG AI to find the cardiac amyloidosis needles in the haystack

Early detection of cardiac amyloidosis is leads to the best outcomes, but it is often missed until later stages. AI is being developed to help detect these patients earlier using ECG and echo.

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Around the web

Radiology Business
Key takeaways from RSNA 2024 for AI, CT, MRI and the radiology staffing shortage

Several key trends were evident at the Radiological Society of North America 2024 meeting, including new CT and MR technology and evolving adoption of artificial intelligence.

Health Imaging
Use of AI opportunistic screening in CT for cardiovascular disease

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.