ArticlePatterns (New York, N.Y.)2023
A deep-learning method for the end-to-end prediction of intracranial aneurysm rupture risk.
Article in Patterns (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled 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.
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
9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.BMC medical imaging · 2024Pooled it
- Systematic Review of Radiomics and Artificial Intelligence in Intracranial Aneurysm Management.Journal of neuroimaging : official journal of the American Society of NeuroimagingPooled it
- Pooled it
- Artificial Intelligence for Intracranial Aneurysm Detection, Rupture-Risk Prediction, and Prognosis Evaluation: Recent Advances and Clinical Integration.Diagnostics (Basel, Switzerland) · 2026Review
- Radiomics and deep learning for intracranial aneurysm rupture-status assessment on CTA/MRA: a multicenter retrospective study.Frontiers in neuroscience · 2026Article
- Convolutional Neural Network (CNN) Model for the Classification of Varieties of Date Palm Fruits (Sensors (Basel, Switzerland) · 2024Article
- Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images.Frontiers in neurology · 2024Review
- Automatic risk prediction of intracranial aneurysm on CTA image with convolutional neural networks and radiomics analysis.Frontiers in neurology · 2023Article
- Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease.Frontiers in human neuroscience · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is critical to accurately predict the rupture risk of an intracranial aneurysm (IA) for timely and appropriate treatment because the fatality rate after rupture is
Indexed as
Identifiers
What OpenQuestion holds
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.