Viz.ai, the leader in AI-powered disease detection and intelligent care coordination, today announced new data from a large aortic dissection artificial intelligence real-world study that supports the use of its artificial intelligence technology for the detection of suspected aortic dissection. Data from the new study, which was presented this week at the 2022 VEITHSymposium™, validates the company’s industry-leading dissection detection algorithm, part of the Viz AORTIC solution.
An abstract by Viz.ai, in collaboration with avicenna.AI, entitled “Real-world validation of a deep learning AI-based detection algorithm for suspected aortic dissection,” reported the performance of the Viz Aortic Dissection Algorithm on 1,303 CT angiography scans collected from over 200 U.S. cities. The algorithm demonstrated a sensitivity of 94.2%, specificity of 97.3%, as well as a positive predictive value of 80.1% and negative predictive value of 99.3%. The authors concluded, “These findings provide significant real-world validation of a deep-learning AI-based detection algorithm for suspected aortic dissection. Automated detection may have a positive downstream effect on patient triage leading to accelerated care coordination, earlier diagnosis, timely initiation of life-saving interventions, and better patient outcomes.”
“My experience as a clinician and AI developer has shown me that care teams need solutions that are not only accurate but that will enable them to be more efficient,” said Dr. Peter Chang, Assistant Professor In-Residence, Radiological Sciences and Co-Director, Center for Artificial Intelligence in Diagnostic Medicine, at UC Irvine. “The application of this aortic algorithm into the workflow has the potential to move the needle for care teams treating this deadly disease.”
Vascular teams are often challenged to make critical treatment decisions with limited information. Viz AORTIC accelerates time-to-notification to specialists giving them access to clinically-relevant imaging and patient information for appropriate patient treatment plans. The solution includes AI-powered alerts, high-fidelity mobile image viewing, relevant clinical information, and HIPAA-compliant communication to facilitate workflow and improve patient care for all aortic conditions.
“Acute aortic dissection is a deadly disease, and mortality for an untreated dissection is about 50% by 24 hours. In 2011, the IRAD investigators showed us that there is often a delayed recognition and treatment of acute aortic dissection, leaving many patients at risk for another cardiovascular event,” said Jayme Strauss, chief clinical officer at Viz.ai. “This new data shows that Viz AORTIC has the power to help care teams coordinate and improve care for these patients in a real-world setting with a diverse patient population.”
For more information on the study results and Viz Aortic, please join a webinar on Wednesday, November 30th at 5pm ET. Register here.
Viz.ai is the pioneer in the use of AI algorithms and machine learning to increase the speed of diagnosis and care, covering more than 200 million lives across 1,200+ hospitals and health systems in the U.S. and Europe. The AI-powered Viz Platform is an intelligent care coordination solution that identifies more patients with a particular disease, informs critical decisions at the point of care, and optimizes care pathways and helps improve outcomes. Backed by clinical data, the Viz Platform delivers significant value to patients, providers, and pharmaceutical and medical device companies. For more information visit viz.ai.
Founded in 2018, avicenna.AI develops medical imaging AI solutions for highly prevalent pathologies. The company uses artificial intelligence and deep learning to optimize many of a radiologist’s manual tasks. Its CINA products leverage deep learning algorithms to identify acute abnormalities and support emergency room triage. avicenna.AI is co-founded by Cyril Di Grandi, who previously co-founded and successfully sold Olea Medical, and Dr. Peter Chang, a radiologist and internationally recognized expert in AI and deep learning.