Rapid ICH uses the latest artificial intelligence technology to quickly triage non-contrast CT (NCCT) cases and notify clinicians of possible intracranial hemorrhage (ICH). It helps stroke and trauma team members on the front lines of patient assessment streamline decision-making and expedite patient care.
Rapid ICH automatically processes images and assesses them for hemorrhage, including intraparenchymal (IPH), intraventricular (IVH), subdural (SDH), and subarachnoid (SAH) subtypes—presenting clear, easy-to-read results that make it easier for physicians to make critical decisions faster.
Rapid ICH uses the latest in artificial intelligence to automatically identify all types of suspected hemorrhage, including IPH, IVH, SDH and SAH, with a sensitivity of 95% and specificity of 94%, excluding hemorrhagic transformations (HTs).
Rapid ICH processes Rapid results in as few as 3 minutes from receipt of scan.
Rapid ICH identifies suspected hemorrhage subtypes, including intraparenchymal (IPH), intraventricular (IVH), subdural (SDH), and subarachnoid (SAH).
Rapid ICH can be used by hospitals, trauma centers and Mobile Stroke Units for quick patient triage and treatment decision-making.
Rapid ICH notifies clinicians of suspected intracranial hemorrhages in all brain regions.
Rapid ICH automatically sends results through PACS, email and the Rapid mobile app.
Rapid ICH identifies the suspicion of suspected intracranial hemorrhage and sends results to trauma and stroke team members in 3 minutes or less.
Leveraging intelligence gained from more than a thousand scans analyzed from hospitals and clinics around the world, Rapid ICH identifies all types of suspected hemorrhage, including IPH, IVH, SDH and SAH, with a sensitivity of 95% and specificity of 94%, excluding hemorrhagic transformations (HTs).
Rapid ICH automatically sends notifications through PACS, email, and the Rapid mobile and web apps. Clinicians have the flexibility to specify the type of alerts they receive—positive only or all.
RapidAI has developed a computerized system based on machine learning that automatically screens CT scans for the presence of intracranial hemorrhage (ICH) immediately after the scan acquisition. This technical paper highlights the importance of this development and the role of state-of-the-art AI systems— from methods and data to suspected ICH identification accuracy and performance.
“…Rapid has been highly accurate… it’s an essential tool.”
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