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. 

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Radiology practice SimonMed Imaging launches breast AI program charging $40 a pop

The Scottsdale, Arizona-based practice follows in the footsteps of RadNet, which has generated millions in revenue from its own artificial intelligence program. 

healthcare executives

Healthcare systems are proceeding apace with GenAI—and learning as they go

Last summer more than 40% of 121 hospital executives surveyed said their organization had already realized a decent ROI in generative AI. However, a C-suite slice of nearly the same size said it was too soon to know for sure. 

Breast cancer AI ribbon pink artificial intelligence

AI effectively flags mammograms of women who would benefit from supplemental MRI

Experts involved in the algorithm's development believe its time-saving potential could help improve both radiologist workflows and patient outcomes. 

Top performing PACS companies based on user feedback

Agfa and Sectra both performed well with end-user satisfaction scores in the 2025 Best in KLAS list of radiology IT systems.

artificial intelligence AI in healthcare

Healthcare AI Digest

Don’t judge DeepSeek on the innovativeness of its programming. Judge it on the degree to which it shakes up the economics of the AI market.

chatgpt artificial intelligence healthcare

How do radiologists feel about utilizing GPT-4 in practice?

In recent years, there has been much talk of the potential for large language models to improve radiology workflows.

medical students AI digital health

To prepare tomorrow’s doctors for evidence-based medicine, instruct today’s med students in dHealth and AI

Medical students are broadly familiar with digital health technologies. Relatedly, they believe AI will play a crucial role in the future of healthcare. These are good signs for the advancement of evidence-based medicine. 

AI-based 3D CTA reconstruction solution scores FDA clearance

Using the new solution, CTA recons are completed in a matter of minutes, not hours.