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. 

Nurses and AI artificial intelligence

4 ways to help nurses make friends with algorithms

Nurses tend to feel optimistic if not exactly excited about AI’s advances into their profession. Those who hold back tend to share a common concern—sacrificing care quality for the sake of tech-enabled efficiency. 

breast cancer screening mammography

AI accurately predicts breast cancer years before diagnosis

This information could help providers personalize breast cancer screening strategies and initiate treatment earlier.

GE HealthCare

GE HealthCare completes $53M acquisition of AI ultrasound business

Based in Cardiff, Wales, seller Intelligent Ultrasound specializes in integrated, AI-driven tools to make scans “smarter and more efficient.” 

ai in healthcare digest blog

Industry Watcher’s Digest

AI didn’t displace the nearly 3,000 people who just lost their jobs at CVS. 

quality imaging appropriateness clinical decision support CAS AUC

Company aiming to automate medical coding in radiology raises $47M

Across its customer base of physician groups, health systems and hospitals, Nym has processed over 6 million charts annually. 

big pharma ai artificial intelligence

In pharma, AI will probably make the big even bigger

Generative AI is fixing to transform the pharmaceutical industry. However, not all adopters will reap rewards in comparable degrees.  

Left, coronary CT angiography of a vessel showing plaque heavy calcium burden. Right, image showing color code of various types of plaque morphology showing the complexity of these lesions. The right image was processed using the FDA cleared, AI-enabled plaque assessment from Elucid.

FDA clears new software for AI-powered CCTA assessments

Elucid's PlaqueIQ was trained to turn CCTA images into interactive 3D reports that help physicians visualize the presence of atherosclerosis.

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GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports

The large language model can also outperform other human providers, radiologists included, new study shows.