ArticleAJNR. American journal of neuroradiology2023
Viz.ai Implementation of Stroke Augmented Intelligence and Communications Platform to Improve Indicators and Outcomes for a Comprehensive Stroke Center and Network.
Article in AJNR. American journal of neuroradiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Automated Emergent Large Vessel Occlusion Detection Using Viz.ai Software and Its Impact on Stroke Workflow Metrics and Patient Outcomes in Stroke Centers: A Systematic Review and Meta-analysis.Translational stroke research · 2025Pooled it
- Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement.Journal of neurointerventional surgery · 2026Trial
- Automated Large Vessel Occlusion Detection Software and Thrombectomy Treatment Times: A Cluster Randomized Clinical Trial.JAMA neurology · 2023Trial
- The implementation of an artificial intelligence-based software for large vessel occlusion stroke improves door-to-puncture time at a comprehensive stroke center.Internal and emergency medicine · 2026Article
- The CBI-M framework for characterization of traumatic brain injury: Evaluation of performance using data from the CENTER-TBI and TRACK-TBI prospective cohort studies.PLoS medicine · 2026Observational
- (Holo-PACS): use of holograms to improve provider acumen when reading clinical radiographic scans.Neurological research · 2026Article
- Implementation of an AI-supported decision-making tool in a high-volume stroke system with routine perfusion imaging.European stroke journal · 2026Article
- Current State of the Clinical Applications of Artificial Intelligence in Stroke: A Literature Review.Brain sciences · 2026Review
- Article
- Artificial Intelligence in Stroke Care: A Narrative Review of Diagnostic, Predictive, and Workflow Applications.Cureus · 2025Review
- Commercialization of medical artificial intelligence technologies: challenges and opportunities.NPJ digital medicine · 2025Article
- Artificial Intelligence in Vascular Neurology: Applications, Challenges, and a Review of AI Tools for Stroke Imaging, Clinical Decision Making, and Outcome Prediction Models.Current neurology and neuroscience reports · 2025Review
- Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology.Cureus · 2025Article
- PFO-ACCESS: Augmenting Communications for Medical Care or Closure in the Evaluation of Patients With Stroke With Cardiac Shunts.Stroke (Hoboken, N.J.) · 2025Article
- Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature.Brain sciences · 2024Review
- VALIDATE-Utilization of the Viz.ai mobile stroke care coordination platform to limit delays in LVO stroke diagnosis and endovascular treatment.Frontiers in stroke · 2024Article
- (VISIION-S): Viz.ai Implementation of Stroke augmented Intelligence and communications platform to improve Indicators and Outcomes for a comprehensive stroke center and Network - Sustainability.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeComprehensive stroke centers continually strive to narrow neurointerventional time metrics. Although process improvements have been put in place to streamline workflows, complex pathways, disparate imaging locations, and fragmented communications all highlight the need for continued improvement. MATERIALS AND
methodsThis Quality Improvement Initiative (VISIION) was implemented to assess our transition to the Viz.ai platform for immediate image review and centralized communication and their effect on key performance indicators in our comprehensive stroke center. We compared periods before and following deployment. Sequential patients having undergone stroke thrombectomy were included. Both direct arriving large-vessel occlusion and Brain Emergency Management Initiative telemedicine transfer large-vessel occlusion cases were assessed as were subgroups of OnHours and OffHours. Text messaging thread counts were compared between time periods to assess communications. Mann-Whitney
resultsEighty-two neurointerventional cases were analyzed pre vs. post time periods: (DALVO-OnHours 7 versus 7, DALVO-OffHours 10 versus 5, BEMI-OnHours 13 versus 6, BEMI-OffHours 17 versus 17). DALVO-OffHours had a 39% door-to-groin reduction (157 versus 95 minutes,
conclusionsThere was an immediate improvement following Viz.ai implementation for both direct arriving and telemedicine transfer thrombectomy cases. In the greatest opportunity subset (direct arriving large-vessel occlusion-OffHours: direct arriving cases requiring team mobilization off-hours), we noted a 39% improvement. With Viz.ai, we noted that immediate access to images and streamlined communications improved door-to-groin time metrics for thrombectomy. These results have implications for future care processes and can be a model for centers striving to optimize workflow and improve thrombectomy timeliness.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.