Even radiologists and AI programs have difficulty spotting the differences between real and synthetic images, but the threat to health care is relatively low.
AI/Machine Learning
AI tumor segmentation of MRI studies shows promise in cases where the use of contrast is not an option.
Radiology is facing growing capacity pressures. Because of scanning technology innovation and longer life expectancies, the sheer volume of medical…
For 30 years, diagnostic imaging has lived inside a fractured ecosystem. PACS, reporting, and worklists each evolved along separate paths…
ncreasingly, hospitals and clinics around the world are using AI-powered imaging software to indicate whether a patient needs care and…
Radiology is bracing for the downstream impact of sweeping policy changes. Recent legislation and updates offer some near-term bright spots,…
AI is no longer a futuristic concept in breast imaging. It is a present-day force, actively transforming how breast cancer…
The explosion of medical imaging data, combined with a persistent shortage of radiologists, is driving the adoption of AI in…
As hyperbolic headlines alternate between warning about the coming AI apocalypse and heralding a coming AI utopia, it’s worth remembering…
CEOs, CFOs, practice managers, billing leaders, and practice owners must stay ahead of emerging trends to remain competitive, efficient, and…