Evidence map›Paper›PMID 41340968›Full record

ReviewCureus2025

Artificial Intelligence in Acute Neuroimaging Pathways: Diagnostic Accuracy, Workflow Performance, and Clinical Outcomes Across CT and MRI in Stroke and Trauma.

Yashwanth Sooranahalli Nabh, Aashish D Rayapati, Ayesha Hamid

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yashwanth Sooranahalli NabhColorectal Surgery, Ashford and St Peter's Hospitals NHS Foundation Trust, Surrey, GBR.
Aashish D RayapatiUrology, East Kent Hospitals University NHS Foundation Trust, Ashford, GBR.
Ayesha HamidTrauma and Orthopaedics, Ashford and St Peter's Hospitals NHS Foundation Trust, Surrey, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review summarizes current evidence on artificial intelligence (AI) applied to emergency neuroimaging for stroke and traumatic brain injury. Across diverse settings, most work focuses on CT-based tools that assist with detection, scoring, triage, and outcome prediction, with MRI used less often for complementary tasks. Findings generally suggest improved diagnostic support and early signals of workflow benefit, though study designs and reporting are heterogeneous. Overall, AI appears ready to augment acute care when integrated into decision pathways, but broader, practice-oriented evaluations with attention to robustness, equity, and real-world implementation remain necessary.

Indexed as

artificial intelligence (ai) in healthcareartificial intelligence ctartificial intelligence in radiologyhealthcare technologymri artificial intelligenceneuroimaging studiesstroketraumatic brain injury

Identifiers

PMID41340968
PMCPMC12671462

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.