Koios Medical, the leader in ultrasound diagnosis decision support software, announces its second 510(k) clearance from the U.S. Food and Drug Administration (FDA). Koios DS (Decision Support) Breast 2.0 is intended for use to assist physicians analyzing breast ultrasound images and aligns a machine learning generated probability of malignancy with the appropriate BI-RADS category. This milestone is an important step in advancing the company's mission of empowering physicians to improve diagnostic accuracy. Now cleared for use at the point of care (or connected to an image viewer for studies stored on PACS), Koios Medical's advancements represent a huge leap forward in using artificial intelligence in healthcare by bringing the power of deep learning to physicians' fingertips. Koios DS Breast 2.0 represents the most advanced AI-based diagnostic technology for ultrasound image analysis to date.
GE Healthcare on Tuesday launched the Edison Developer program to make it easier to integrate new AI-driven applications directly into healthcare provider workflows. The new program is based on Edison, the AI platform GE Healthcare launched last year to leverage data from imaging devices. What is AI? Everything you need to know about Artificial Intelligence As the market for AI-based products and services for the health sector heats up, GE Healthcare says its aim with the Edison Developer program is to accelerate the adoption of AI among health providers. While there's interest in adopting these technologies, it can be a slow, disjointed and complex process, GE says. The new program will simplify the process by deeply integrating market-ready AI applications into existing GE Healthcare offerings, in the cloud cloud and at the network edge offerings as well as in medical devices.
If you have something important to share but no way to distribute it to people, what good is it? Similarly, when a developer creates an innovative application, the platform is just as important as the application itself. With the new Edison Developer Program, GE Healthcare is selecting market-ready independent software vendors (ISVs) and developers to leverage the power of the Edison platform. This opportunity may help them to achieve faster adoption and experience commercial growth for their healthcare applications. It also fosters innovation within GE Healthcare's intelligence platform, where applications are built specifically for the needs of healthcare.
Fujifilm Medical Systems U.S.A. is showcasing REiLI, the company's global medical imaging and informatics artificial intelligence (AI) technology initiative at the 2019 Radiological Society of North America's (RSNA) annual meeting. "At RSNA 2019, we look forward to sharing the AI insights and advances we've made by working closely with clinical and research partners for several years," said Takuya Shimomura, chief technology officer and executive director, Fujifilm. "Ultimately, the long-term goal of our AI initiative is to help providers make better decisions that improve patient lives." Under the REiLI brand, Fujifilm is developing AI technologies that strongly support diagnostic imaging workflow, leveraging the combination of its deep learning innovations and distinct image processing heritage. Applications currently in development include, but are not limited to: Region Recognition, an AI technology that helps to accurately recognize and consistently extract organ regions, regardless of deviations in shape, presence or absence of disease, and imaging conditions; Computer Aided Detection, an AI technology to reduce the time of image interpretation and support radiologists' clinical decision making; Workflow Support, using AI technology to realize optimal study prioritization, alert communications of AI findings, and report population automation.
Much has been made in recent years about the explosion of artificial intelligence (AI) in radiology and how it might impact the role of radiologists themselves. But artificial intelligence is, by definition, artificial. In an itnTV video from the 2018 Radiological Society of North America (RSNA) annual meeting, ITN Contributing Editor Greg Freiherr explored how AI cannot take the place of people, but it can help people get what they need. You can view the video at https://bit.ly/2FMgDvH. "I doubt any radiologist could build an MR or a CT scanner from scratch. They probably couldn't even build it from pieces," said Bradley J. Erickson, M.D., Ph.D., chair, radiology informatics/associate chair, research-radiology at the Mayo Clinic in Rochester, Minn., in the itnTV video.