The Edinburgh-based business made the announcement on Jan. 18, noting that the acquisition will build on the company’s goals to “improve the lives of patients and populations by unlocking the adoption and benefits of medical imaging AI.” 

While there are numerous formulas to help guide providers in managing incidental findings, there is limited data available on the outcomes and cost-effectiveness of the subsequent evaluations that follow.

When choosing and implementing an electronic health record system, it is important to consider how the system’s architecture might affect providers’ decision-making. 

Radiology is one of the few medical specialties that allow for location flexibility, but what clinicians gain in the convenience of working from home, they lose in the form of fulfillment that only physical presence can offer, some argue. 

A recent analysis found that a significant amount of studies do not provide information pertaining to their raw data, source code or model. As a result, up to 97% of these studies do not produce systems that are fit to be used in real-world clinical scenarios. 

Sanjay Parekh, PhD, senior market analyst with Signify Research, explains how some radiology AI is being adopted outside of radiology departments to improve care.

In this interactive ebook, we bring together stories, interviews, webinars, podcasts, case studies and white papers that shine light on how enterprise imaging is making care more insightful, efficient, effective, collaborative, robust, cloud-enabled and even more affordable.

Use of the template, which included PCP notifications, also resulted in an increase of biochemical testing, follow-up imaging and specialist referrals in patients with incidental adrenal masses.