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 software improves diagnosis of lung conditions when contrast cannot be used

New software could improve diagnosis of lung conditions for patients who cannot tolerate contrast dye

The machine learning-based software uses a formula called the Integrated Jacobian Formulation to calculate lung volume based on metrics derived from imaging taken during inhalation and exhalation.

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.

FDA clears advanced AI model for predicting heart failure risk

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.

AI-powered coronary plaque assessments show ‘strong agreement’ with IVUS

HeartFlow's noninvasive Plaque Analysis technology, which uses AI to evaluate CCTA images, delivered assessments that mostly lined up with IVUS results.

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

bipartisan house task force on artificial intelligence

About that bipartisan $32B ‘roadmap’ for AI policy: What’s in it for healthcare?

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

AI model for ankle stress radiography could reduce radiologists’ workload by average of 70%

Interpreting such exams can be a “subjective and time-consuming task,” researchers detailed in Academic Radiology.

AI-based CAD assessments dramatically improve vascular surgery outcomes

PAD patients evaluated with HeartFlow's noninvasive FFR_CTAnalysis technology prior to surgery experienced much better outcomes, including a 63% lower risk of all-cause mortality after five years.

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.

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