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.

The new algorithm from Implicity evaluates implantable device data and monitors patients for changes that suggest they could experience severe heart failure symptoms in the near future. It was designed to alert clinicians up to weeks in advance.

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Buzzworthy developments of the past few days.

bipartisan house task force on artificial intelligence

This week Washington took a major step toward nailing down a solid game plan on federal AI spending for everything outside of defense.

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.

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

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Buzzworthy developments of the past few days.

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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.

artificial intelligence healthcare

Buzzworthy developments of the past few days.

AI in nursing

Most nurses are at least somewhat skittish about the march of AI into their workflows. Their main concerns revolve around the technology’s potential to slap back the human touch in care delivery.

AI models can be trained to predict outcomes for patients receiving thrombolysis for acute ischemic stroke (AIS), according to a new study published in the Journal of the Neurological Sciences.

The Wuhan coronavirus has already infected thousands of people around the world, with its death toll quickly approaching triple digits. Can AI prove to be a valuable tool in studying the spread of such illnesses?

When research teams are developing deep learning models, they have to make certain decisions about the image resolutions used in their work. For instance, should they always aim to use the largest images possible? Or are there times when smaller images can get the job done?  

Dermatologists need to be more involved in the development of AI technologies designed to evaluate skin cancer, according to a new analysis published in the Journal of the American Academy of Dermatology.

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The new algorithm from Implicity evaluates implantable device data and monitors patients for changes that suggest they could experience severe heart failure symptoms in the near future. It was designed to alert clinicians up to weeks in advance.

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

The popular AI chatbot's performance highlighted both its strengths and its weaknesses. It can answer multiple-choice questions, for example, but it struggles with consistency.