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.

ai artificial intelligence in healthcare

6 ways to convert GenAI adoption into real business value

Using the technology and making it work for purpose are two different things. And the U.S. leads all countries in terms of full implementation, at 24% (vs. 19% for China).

AI tool's supplemental MRI recs help detect 4 times more breast cancers than density measures

What’s more, many of the cancers detected were invasive or multifocal, making their detection more timely.

How does AI TI-RADS compare to other thyroid nodule risk stratification systems?

Experts are hopeful that the reporting and data system could simplify the risk stratification of thyroid nodules in the future.

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

artificial intelligence in healthcare oncology cancer care

3 aspects of cancer care ripe for AI augmentation

Oncologists using or considering AI tools tend to agree among themselves on three points of ethics—and to recognize the same number of ways AI could help advance the state of patient care.

artificial intelligence AI in healthcare

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

Elusive quadruple aim revisited for the generative AI era

Is U.S. healthcare capable of achieving its own quadruple aim? Or is that ideal destined to remain a perpetual pursuit, always chased but never really caught?

Thomas Maddox, MD, explains some of the new, innovative technologies people should watch for in cardiology. He said some of these may define how cardiologist practice medicine in the next couple years.

Remote monitoring, AI to play key roles in the future of cardiology

Serious changes could be coming to a cardiology practice near you.

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