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.

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.
Newswatch: AI for Medicare folk, AI uncertainty at the FDA, generative ghosts, more
AI is making patient financial advisors of hospital administrators who used to work in revenue cycle management.
Deep learning reconstruction enables 5-minute MRI scans
New research in the American Journal of Roentgenology details a deep learning super-resolution image reconstruction technique that opens the door for accelerated imaging of the knee.
Feds should take page from EHRs, creating ‘Meaningful Use’ program to spur AI adoption, Rad Partners leaders say
"Using a similar approach of front-loaded, declining incentives, an AI-focused program could help accelerate adoption and implementation," write Richard Heller and Nina Kottler.
The future of AI in nursing is already here yet still on the way
Is AI changing the profession of nursing—or are nurses changing AI?

Charles E. Kahn, Jr., MD, MS, Editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine. He has been heavily involved in radiology informatics and has seen up close the evolution of radiology toward deeper integration with AI. #RSNA

VIDEO: Use cases and implementation strategies for radiology artificial intelligence

Charles Kahn, Jr., MD, editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, explains the work involved integrating AI in radiology systems and the role of AI in augmenting patient care.

VIDEO: Assessing radiology AI and understanding programatic bias

Charles E. Kahn, Jr., MD, MS, editor of the the RSNA journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, discusses the need to validate AI algorithms with your own patient population data.

Prostate cancer detection boosted with computer assistance

The addition of computer-aided diagnostic generated MRI series could help radiologists identify clinically significant prostate cancer more frequently.

AI software's pediatric fracture detection in line with that of radiologists

An artificial intelligence system that is currently commercially available for use in adults could also have applications in a pediatric population, according to a new study in Pediatric Radiology.

Female Medical Research Scientist Working with Brain Scans

FDA approves AI analysis of high-grade gliomas

An AI startup in the neuro-oncology space has received the government’s go-ahead to market software for analyzing certain fast-growing brain tumors on MRI.

Oncology imaging AI growing fast yet still in its infancy

If generalizable AI models are to meaningfully contribute to precision cancer care, they’ll need to incorporate not only imaging data but also digitalized clinical notes, biomarker assays and monitor readouts.

Radiomics-based models can detect pancreatic cancer well before clinical diagnosis

Recently a radiomics-based machine learning model proved highly accurate at predicting which patients would develop pancreatic cancer three to 36 months after abdominal CT imaging.

Google Cloud intros ambitious branch dedicated to medical imaging

A Big Four tech company has launched a platform it hopes will accelerate data interoperability and AI adoption in, specifically, medical imaging.

Artificial Intelligence

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

Newswatch: AI for Medicare folk, AI uncertainty at the FDA, generative ghosts, more

Deep learning reconstruction enables 5-minute MRI scans

Feds should take page from EHRs, creating ‘Meaningful Use’ program to spur AI adoption, Rad Partners leaders say

The future of AI in nursing is already here yet still on the way