Evidence map›Paper›PMID 39982556›Full record

ArticleNeurosurgical review2025

Artificial intelligence in neurovascular decision-making: a comparative analysis of ChatGPT-4 and multidisciplinary expert recommendations for unruptured intracranial aneurysms.

Alexis Hadjiathanasiou, Leonie Goelz, Florian Muhn, Rebecca Heinz, Lutz Kreißl, Paul Sparenberg, Johannes Lemcke, Ingo Schmehl, Sven Mutze, Patrick Schuss

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Neurosurgical review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
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

10 authors.

Alexis HadjiathanasiouDepartment of Neurosurgery, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany. alexis.hadjiathanasiou@ukb.de.
Leonie GoelzDepartment of Radiology and Neuroradiology, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Florian MuhnDepartment of Neurology, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Rebecca HeinzDepartment of Neurosurgery, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Lutz KreißlDepartment of Radiology and Neuroradiology, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Paul SparenbergDepartment of Neurology, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Johannes LemckeDepartment of Neurosurgery, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Ingo SchmehlDepartment of Neurology, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Sven MutzeDepartment of Radiology and Neuroradiology, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.
Patrick SchussDepartment of Neurosurgery, BG Klinikum Unfallkrankenhaus Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the multidisciplinary treatment of cerebrovascular diseases, specialists from different disciplines strive to develop patient-specific treatment recommendations. ChatGPT is a natural language processing chatbot with increasing applicability in medical practice. This study evaluates ChatGPT's ability to provide treatment recommendations for patients with unruptured intracranial aneurysms (UIA). Anonymized patient data and radiological reports of 20 patients with UIAs were provided to GPT-4 in a standardized format and used to generate a treatment recommendation for different clinical scenarios. GPT-4 responses were evaluated by a multidisciplinary panel of specialists by means of the Likert scale and subsequently benchmarked against the Unruptured Intracranial Aneurysm Treatment Score (UIATS) as well as the actual treatment decision made by the multidisciplinary institutional neurovascular board (INVB). Agreement between expert raters was measured using linear weighted Fleiss-Kappa coefficient. GPT-4 analyzed individual pathological features of the radiological reports and formulated a corresponding assessment for each aspect. None of the recommendations generated reflected evidence of factual hallucination, although in 25% of the case studies no specific recommendation could be derived from the GPT-4 responses. The expert panel rated the overall quality of the GPT-4 recommendations with a median of 3.4 out of 5 points. The GPT-4 recommendations were congruent with those of the INBI in 65% of cases. Interrater reliability among experts showed moderate to low agreement in the assessment of AI-assisted decision making. GPT-4 appears to be able to process clinical information about UIAs and generate treatment recommendations. However, the level of ambiguity and the utilization of scientific evidence in the recommendations are not yet patient/case specific enough to substitute the decision-making of a multidisciplinary neurovascular board. A prospective evaluation of GPT-4 competence as a companion in decision-making panels is deemed necessary.

Indexed as

Artificial IntelligenceClinical Decision-MakingDecision MakingIntracranial AneurysmNatural Language ProcessingAdultAgedFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedAneurysm treatment decisionArtificial intelligenceChatGPTInstitutional neurovascular board

Identifiers

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Textmetadata
Read underepoch 390

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.