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.

Deep learning-based reconstructions nearly halve acquisition time of spinal MRIs
The accelerated exam does not come at the expense of image quality, according to new work published in Academic Radiology.
Industry Watcher’s Digest
An influential industry group, AdvaMed, really likes President-Elect Trump’s choice of Dr. Oz for CMS administrator.
5 ways to let AI raise patient satisfaction, elevate provider performance
It’s been years since AI proponents started promising big returns on healthcare providers’ investments in the technology. The results have yet to catch up with the pitches. What’s the holdup?
Experts highlight 'significant concerns' with fluctuating accuracy of popular large language models
As these models continue to advance, it is important to understand how their performance holds up over time.
Startup aiming to automate 90% of imaging workflows, creating an ‘AI radiology resident,’ raises $23M
Software engineer and CEO Shiva Suri says he got the idea for New Lantern after watching his radiologist mother bogged down by administrative tasks.

How AI will impact hospital and health system workforces

Hospitals of the future will operate very differently than today thanks to the boom in AI, according to the American Hospital Association.

October 3, 2019

AI takes 10 seconds to diagnose pneumonia on chest x-rays

A new AI platform takes a mere 10 seconds to identify key findings on a patient’s chest x-ray, compared to the 20 minutes typically required.

October 2, 2019

Radiology societies team up for new statement on ethics of AI

Numerous imaging societies, including the American College of Radiology (ACR) and RSNA, have published a new statement on the ethical use of AI in radiology.

October 1, 2019

Q&A: J. Raymond Geis on ethical AI in radiology

J. Raymond Geis, MD, senior scientist at the ACR Data Science Institute, spoke with HealthImaging about the recently published multisociety statement on ethical AI in radiology.

October 1, 2019

Imaging societies publish new ethics of AI in radiology document

“The radiology community needs an ethical framework to help steer technological development, influence how different stakeholders respond to and use AI, and implement these tools to make the best decisions for—and increasingly with—patients," said one of the paper's lead contributors, Raymond Geis, MD.

September 30, 2019

Physical therapy a potential application for ‘sensitive’ artificial skin

Engineers and roboticists in Europe have invented an artificial skin that can provide wearers with haptic feedback—replicating the human sense of touch—for potential applications in various fields, including medical rehabilitation and physical therapy.

September 27, 2019

AI phone app IDs implantable cardiac devices on chest x-rays

Researchers out of the U.S. have created an AI smartphone app to automatically identify cardiac devices—such as pacemakers—on chest x-rays, describing their process in JACC: Electrophysiology.

September 26, 2019

FDA clears modules for AI-based CT solution from Siemens Healthineers

Siemens Healthineers announced Thursday, Sept. 26, that it has received FDA clearance for three modules of the company’s AI-Rad Companion Chest CT software.

September 26, 2019

Artificial Intelligence

Deep learning-based reconstructions nearly halve acquisition time of spinal MRIs

Industry Watcher’s Digest

5 ways to let AI raise patient satisfaction, elevate provider performance

Experts highlight 'significant concerns' with fluctuating accuracy of popular large language models

Startup aiming to automate 90% of imaging workflows, creating an ‘AI radiology resident,’ raises $23M