NinesAI is a software tool that uses artificial intelligence to automatically analyze head CT images for signs of intracranial hemorrhage and mass effect. It helps prioritize critical cases by notifying radiologists of potential emergencies to assist in timely and effective patient care. The software works alongside standard workflows and does not replace full clinical evaluation or diagnosis.
NinesAI is a parallel workflow tool indicated for use by hospital networks and trained clinicians to identify images of specific patients to a radiologist, independent of standard of care workflow, to aid in prioritizing and performing the radiological review. It analyzes head CT images for findings suggestive of a pre-specified emergent clinical condition, specifically assessing suspected presence of intracranial hemorrhage and/or mass effect and not for diagnostic use beyond notification.
NinesAI employs artificial intelligence algorithms trained on a database of radiological images to analyze non-contrast head CT scans for intracranial hemorrhage and mass effect. The system includes image analysis software and a workstation module for alerting radiologists, using machine learning algorithms and notification technology to assist in triage.
Performance testing included software verification and validation, retrospective performance trials for each algorithm analyzing sensitivity and specificity, and a time benefit analysis. Sensitivity was 0.899 for intracranial hemorrhage and 0.964 for mass effect; specificity was 0.974 and 0.911, respectively. Time-to-notification was significantly faster than standard time-to-open-dictation, supporting efficacy and safety.
No predicate devices specified
Submission
12/3/2019
FDA Approval
4/21/2020
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