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.

Hospital explores using AI to autonomously order imaging exams in the emergency department

Machine learning could streamline care for 22% of visits while making results available earlier by 165 minutes per affected patient, experts wrote in JAMA.

Image quality is not an issue for AI model that detects pulmonary embolisms on CT

CTPA is the standard of care for diagnosing PE, but suboptimal scans make it difficult to reach a diagnosis. A new Clinical Imaging study tests the effectiveness of AI when image quality is lacking.

Small airway disease a potential long-lasting effect from COVID-19, new Radiology study warns

A new prospective study from the University of Iowa compared expiratory chest CT from post-COVID patients and a healthy control group, unearthing stark differences.

AI tool achieves excellent agreement for knee OA severity classification

Many decision support tools catered to knee osteoarthritis have emerged in recent years, but external validation that ensures these algorithms can operate in a clinical setting has been lacking.

AI adoption is lagging in radiology and the rest of healthcare. Brookings experts answer why

Lack of trust in algorithms, challenges in data collection, and regulatory barriers are all impeding progress, the Washington-based research outfit argued.

AI-powered ECG analysis could boost care for patients with hypertrophic cardiomyopathy

Advanced algorithms can pick up on key details in a 12-lead ECG that human readers are unable to see.

AFib, AI and heart-healthy diets: European Society of Cardiology previews EHRA 2022

The European Heart Rhythm Association's annual conference is headed to Denmark.

FDA greenlights AI software that detects fractures and traumatic injuries

A study published by Boston University School of Medicine revealed that fracture detection improved for readers by 10.4% with BoneView AI's assistance.

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?