AI-Based Radiology Solutions to Improve ICU Care
Alumni
X-rays are extremely important to answer specific diagnostic questions in medicine. For patients in the intensive care unit (ICU), doctors may order a new x-ray every day, and correct interpretation is critical. It would be ideal if a radiologist could immediately assess every image, but this is simply not possible in many hospitals: in Germany 60 % of hospitals do not have a radiologist on-call to assess x-rays at night or on the weekends.
As a result, the medical staff on-site must interpret the images themselves, and if expertise is lacking, the error rate is subsequently high. These errors can delay diagnosis, lengthen hospital stays, or lead to suboptimal therapy, which can additionally burden patients and the healthcare system.
Keno Bressem
(Charité, German Heart Center Munich)
Project Lead
Stefan Niehues
(Charité)
Project Lead
rAIdiance is powered by an interdisciplinary team with many years of experience in radiology and AI. The team also works closely with PACS vendors and expert advisors in software development, regulatory affairs, and market access.