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.

AI-directed scan protocols cut back on unnecessary MRI sequences
Artificial intelligence could serve as an effective tool for determining which patients may need additional breast MRI sequences mid-protocol.
AI newswatch: Nurses want in, transcriptionists on the way out, blockchain going up, more
If doctors are the heart of the hospital, nurses are surely the soul. And if that’s so, today’s AI has to be something like a nutritional supplement for the brains of the operation.
Real-world use of generative AI boosts radiologist productivity by up to 40%
“For me and my colleagues, it’s not an exaggeration to say that it doubled our efficiency," says radiologist Samir F. Abboud, MD, chief of emergency radiology at Northwestern.
Research review: Patients have understandably mixed feelings about AI in healthcare
A new review of the relevant scientific literature suggests many if not most patients are aware that healthcare AI’s emerging benefits exist side-by-side with its persistent uncertainties.
AI detects twice as many incidental lesions as radiologists
Prior research has suggested that these incidental lesions turn out to be cancerous in up to 70% of cases, making their timely detection critical.

deep learning algorithm slashes radiation dose during neck CT scans

Deep learning denoising software can cut radiation exposure to 25% of conventional doses during neck CT

And the dose reduction can be achieved without sacrificing image quality, a new analysis shows.

'Too many cooks in the kitchen': How AI is both helpful and a hindrance to radiologists

Recent research suggests that, in many cases, radiologist performance only improves minimally with AI assistance.

Machine learning helps experts identify ADHD biomarkers on MRI scans

Experts have identified numerous white matter features, in addition to changes in white matter tracts that occur over time, which they believe are more common among people with ADHD.

Age, race and density status influence AI performance on mammogram reads

Although studies have shown AI to be effective as a support tool, several have also highlighted issues related to the potential for bias in algorithms that have not been trained on diverse datasets.

artificial intelligence AI in healthcare

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9 notable quotes from 1 big day at an epicenter of AI in healthcare

As AI continues augmenting the expertise of healthcare professionals, look for it to go further and do nothing less than “enhance humanity.”

Many imaging journals still lack policies on the use of AI in manuscript writing

Nearly 40% of MEDLINE-indexed radiology journals do not provide guidelines for AI generated content.

Philips presents study results at Heart Rhythm annual meeting demonstrating benefits of its AI-powered cardiac monitoring solutions

With cardiovascular disease on the rise, clinicians and health systems continue to look for ways to deliver high-quality care that is both timely and cost-effective.

Artificial Intelligence

AI-directed scan protocols cut back on unnecessary MRI sequences

AI newswatch: Nurses want in, transcriptionists on the way out, blockchain going up, more

Real-world use of generative AI boosts radiologist productivity by up to 40%

Research review: Patients have understandably mixed feelings about AI in healthcare

AI detects twice as many incidental lesions as radiologists