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Faster stroke treatment followed e-Stroke, RapidAI and Viz

In studies that NICE reviewed, stroke treatment came faster or more often after centers adopted e-Stroke, RapidAI or Viz. NICE could not tell how much was due to the software.

  • Not rated a person

    NICE gives no size for the faster access to treatment and cannot say how much of it is due to the software.

Depth runs from 1, a convenience or time saved, to 5, a life or a livelihood preserved.

Status
Reported and intended benefits.
Evidence

found, the grade of this recordstudiedreportedclaimed

Two independent assessment reports support the benefit.

Compared with

Time to treatment before centers adopted the software, in seven observational studies. Measured.

The system’s part
Not isolated. The studies compared periods before and after centers adopted the software, while other parts of stroke care also changed. NICE notes that the image-sharing function may drive part of the benefit and that the software uses fixed algorithms derived with AI.
Limits
Not yet checked.
Costs and harms
Not yet checked.
Later
Not yet checked.
Benefit type
Reduced Task Time
System
e-Stroke, RapidAI and Viz (AI-derived software for CT brain scans in suspected stroke)
Made by
Brainomix (e-Stroke), iSchemaView (RapidAI) and Viz.ai (Viz)
Used by
NHS stroke centers in England, with AI decision support live at 99 of 107 stroke units
Where
England, United Kingdom
Stage
In routine use
Date
, when the source was published
Kind
Aggregate result
Broad benefit
Identifying Objects, Actions, and Events, Communicating with Supervisors, Peers, or Subordinates
Collections
Scrutiny and findings
Last revised
31 October 2026

Sources

  1. Assessment report, by authors with no tie to the system.

    National Institute for Health and Care Excellence. Artificial intelligence (AI)-derived software to help clinical decision making in stroke. HealthTech guidance HTG708 (formerly DG57), section 1: Recommendations. 23 January 2024, last updated 2 May 2024.

    Some studies on 3 technologies (e-Stroke, RapidAI and Viz) in clinical practice suggest that people had faster or greater access to treatment after using the software, but it is unclear to what extent this is an effect of the software.
  2. Assessment report, by authors with no tie to the system.

    National Institute for Health and Care Excellence. HTG708, section 3: Committee discussion. 23 January 2024, last updated 2 May 2024.

    In the EAG's initial review there were 7 observational studies that compared time to treatment before and after implementing AI-derived software in clinical practice, assessing e-Stroke, RapidAI and Viz. Most of the studies suggested that time to treatment for people who had thrombectomy or thrombolysis had reduced after implementing the software.

Details

AI system

Workflow

The software flagged findings on CT brain scans for review by a healthcare professional. The software sent scan images quickly between hospitals for remote review.

Follow-up

Conditions for replication

Centers keep their existing scan reporting protocols. Shared images are of sufficient quality for remote review.

Entry details

Sector

Healthcare (acute stroke care).

Purpose

Brainomix, iSchemaView and Viz.ai built e-Stroke, RapidAI and Viz to analyze CT brain scans for signs of stroke and to speed treatment decisions.

Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, AI contribution, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.

Cite this record

Peter H. Vartanian. (2026). Faster stroke treatment followed e-Stroke, RapidAI and Viz (AIBD-0737). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0737.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)

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