Amy Thompson, a senior analyst at Signify Research, explains what she is seeing in the market for radiology PACS and IT systems. She said the biggest overall, strategic technology trends are wider adoption of enterprise imaging, migration to cloud data storage, adoption of artificial intelligence (AI), streamlining workflow, and implementing structured reporting.

DiA Imaging Analysis, an Israel-based healthcare technology company, has gained U.S. Food and Drug Administration (FDA) clearance for LVivo IQS, a new software solution designed to help users acquire high-quality echocardiography images, regardless of their experience.

The integration of artificial intelligence into radiology PACS and enterprise imaging systems has become a big topic of discussion with IT vendors over the past couple years. This has become a bigger question from hospitals and radiology groups as there are now about 400 radiology related AI algorithms that have U.S. Food and Drug Administration...

Text-generating AI models, such as ChatGPT, have the potential to “revolutionise the field of medical writing” by automating tasks and increasing efficiency throughout the writing process.

An AI tool named “Sybil” was able to forecast both short- and long-term lung cancer risk based on a single low-dose CT (LDCT) scan, researchers reported.

In efforts to speed workflow, improve patient care and augment an increasingly shorthanded clinical workforce, AI is starting to see wider adoption across healthcare. But there are questions regarding who is liable if an AI application fails and it results in a malpractice lawsuit.

Two artificial intelligence (AI) programs, including ChatGPT, have passed the U.S. Medical Licensing Examination (USMLE), according to two recent papers.

An imaging industry supplier best known for a widely adopted radiology reporting platform is partnering on radiological artificial intelligence with a company that pioneered GPUs and accelerated computing.Together the companies are aiming to put AI-based diagnostic tools “directly into the hands of radiologists and other clinicians at scale, enabling the delivery of improved patient care...

The healthcare industry has a lot of hope for machine learning solutions across patient care. However, there are many barriers to widespread adoption keeping machine learning from being implemented into clinical practice.

A new artificial intelligence (AI) model from researchers at MIT can detect Parkinson’s disease, a notoriously difficult disease to detect, through breathing patterns. The tool could help alleviate the disease onset gap between when symptoms of Parkinson’s first appear and when most people receive a diagnosis. The MIT team that developed the AI model uses...