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.

Is AI just what the doctor ordered for the radiologist shortage? Yes and no
AI shines in radiology when tasked with interpreting images of patients whose odds of illness are either very high or very low. In these cases, the technology could help mitigate burnout and supplement staffing.
AI predicts pediatric cancer recurrence with impressive accuracy
Researchers have developed a deep learning model that can spot longitudinal changes in patients' brain imaging that could be indicative of cancer recurrence.
AI helps cardiologists terminate AFib for good with ablation
Advanced AI can provide real-time feedback to cardiologists, helping them deliver high-quality care.
Big-name healthcare orgs tap AI to improve breast imaging workflows
These moves come as healthcare organizations are increasingly seeking ways to integrate artificial intelligence into daily clinical duties.
Congress should relax budget neutrality to pay for imaging AI, industry lobbying group urges
"As the nation’s largest payer of healthcare, Medicare’s policies on coverage and payment for AI technologies are especially critical," AdvaMed says.

New AI model predicts heart failure hospitalizations

Detecting heart failure issues early on, one researcher observed, can improve patient care and hospital efficiency at the same time.

Treatable tumor models grown in the lab

The bioprinted replicas can preview a given tumor’s reaction to specific therapies and combinations thereof.

Nanox sees stock slide after FDA finds deficiencies in application for novel imaging system

The Israel-based radiology startup said it plans to respond by the 180-day deadline, but did not indicate whether the rollout of its technology will be postponed.

10 questions clinicians—and patients—ought to ask about every AI they encounter

Technology educators, tech-policy wonks and hospital clinical leaders from three countries have collaborated to produce a helpful guide for end-users of healthcare-specific AI tools—and the patients they serve.

3 noteworthy developments in emerging medical technologies

While big breakthroughs in healthcare AI seem to have slowed in recent weeks, those involving other hot technologies have kept the content coming for publishers of peer-reviewed medical journals.

Deep learning valuable for assessing coronary plaques on CCTA scans

The tool outperformed one board-certified radiologist while rivaling a cardiac specialist with 20-plus years of experience.

Cardiovascular imaging specialists raise $33M to ramp up use of AI platforms

The Blue Venture Fund, a collaboration of dozens of Blue Cross Blue Shield companies, led the funding round.

HIMSS speakers see standards, possibly ‘nutrition labels’ in healthcare AI’s future

Freely hope for the best, but diligently prepare for the worst. Applied to end users of healthcare AI, that adage could have been a key takeaway at last week’s annual meeting of HIMSS in Las Vegas.

Artificial Intelligence

Is AI just what the doctor ordered for the radiologist shortage? Yes and no

AI predicts pediatric cancer recurrence with impressive accuracy

AI helps cardiologists terminate AFib for good with ablation

Big-name healthcare orgs tap AI to improve breast imaging workflows

Congress should relax budget neutrality to pay for imaging AI, industry lobbying group urges