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.

Startup seeking to simplify medical imaging referrals raises $101M
Tennr uses an “enterprise orchestration engine” and series of specialized language models, trained on the nuances of processing documentation against payer criteria.
AI model gets helpful heart assessments out of nongated CT scans
"Using AI for tasks like CAC detection can help shift medicine from a reactive approach to the proactive prevention of disease," one researcher said.
Led by notable names in radiology, imaging AI firm HOPPR raises nearly $32M
Founded in 2019 and based in Chicago, the vendor offers a “leading” infrastructure platform for building, refining and deploying large-scale AI models in medical imaging.
Healthcare AI today: Dangerous LLMs, self-training AI—and is AI good for what ails healthcare?
If an individual is at all susceptible to mental unwellness, overuse of a talkative LLM could push him or her over the edge. Maybe literally.
Could the metaverse be the new radiology education classroom?
According to new data, the simulated virtual environment may be just as effective of a setting as the classroom for problem-based learning.

AI software that triages x-rays for pneumothorax receives FDA clearance

The new algorithm flags chest x-rays when it detects pneumothorax and notifies physicians of any suspicious findings.

Imaging artificial intelligence startup Qure.ai raises $40M in new funding

First launched in 2016, the AI firm offers products that help docs read and interpret X-rays, CTs and ultrasounds “in less than a minute."

AI shows promise as a second reader for breast cancer detection

A commercial artificial intelligence system correctly identified nearly 88% of screen-detected cancers and 45% of interval cancers, according to a major study published in Radiology.

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AI assists radiologists in detecting fractures, improves workflow

Research published recently in Radiology found comparable sensitivity and specificity between artificial intelligence and clinicians for fracture detection.

radiology reporting EHR health record CDS AUC

Scaling structured radiology reporting template use across multiple health systems to build a data registry

Pennsylvania imaging experts offered several key lessons learned, including the need to engage rads and continuously monitor data accuracy.

Misuse of public imaging data is producing 'overly optimistic' results in machine learning research

"This research aims to raise a red flag regarding naive off-label usage of open-access data in the development of machine-learning algorithms," experts involved in the study said.

Radiology groups urge Congress to address scarcity of AI solutions in pediatric care

The Society for Pediatric Radiology and ACR want lawmakers to draft healthcare policies that encourage innovation in artificial intelligence to address this gap.

Private equity makes ‘strategic growth investment’ in heart CT, MR firm Circle Cardiovascular Imaging

Financial terms were not disclosed, but the two said the funds will fuel future expansion of its AI-based products, used for reading, reporting and processing images.

Artificial Intelligence

Startup seeking to simplify medical imaging referrals raises $101M

AI model gets helpful heart assessments out of nongated CT scans

Led by notable names in radiology, imaging AI firm HOPPR raises nearly $32M

Healthcare AI today: Dangerous LLMs, self-training AI—and is AI good for what ails healthcare?

Could the metaverse be the new radiology education classroom?