Imaging

The American College of Radiology's ARCH-AI initiative is billed as the first-ever such framework, designed to help imaging providers deploy artificial intelligence more safely.

Using the technology can be daunting because it involves considerable time and careful results management – but augmenting it with AI image enhancement software has made a big difference for its radiologists.

AI could identify early signs of heart disease and even Alzheimer’s in ocular images. But Kerry Goetz, associate director, NEI Office of Data Science and Health Informatics, says a lack of interoperability keeps this image data out of EHRs.  

Dr. Benoit Desjardins, professor of radiology at Penn Medicine, describes how automation and AI-powered analysis are transforming clinical imaging workflows.  

Robotic-assisted bronchoscopy enables doctors to perform minimally invasive biopsies in distant areas of the lungs, including small nodules in the peripheral regions.

A randomized clinical vignette survey across more than a dozen states, with hospitalists, NPs and PAs taking part, evaluated systematically biased algorithms and how clinicians make decisions with image-based AI guides.

Also, FPT has closed a deal to exclusively distribute Nipro's blood glucose monitors in Vietnam.

Also, two hospitals under SingHealth have started adopting Lunit's AI chest X-ray solution.

Also, regional health services in Western Australia are rolling out Magentus' oncology patient record.

Thanks to machine learning, pocket-sized cardiac sonography can help any medical professional make real-time cardiac-care decisions in acute, field, EMS and rural settings, says UltraSight CEO and cofounder Davidi Vortman.