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Artificial intelligence and machine learning in aneurysmal subarachnoid hemorrhage: Future promises, perils, and
Saif Salman1, Qiangqiang Gu2, Rohan Sharma1
1Department of Neurological Surgery, Neurology and Critical Care, Mayo Clinic, Jacksonville, FL 32224, United States of America.
Journal of the Neurological Sciences
|October 21, 2023
Summary
Artificial intelligence (AI) and machine learning (ML) show promise in improving outcomes for patients with aneurysmal subarachnoid hemorrhage (SAH). These technologies can enhance detection, prediction, and intervention for this critical condition.
Area of Science:
- Neurology
- Medical Imaging
- Artificial Intelligence
Background:
- Aneurysmal subarachnoid hemorrhage (SAH) is a severe stroke subtype with high mortality.
- Current management requires timely detection, segmentation, and clinical decision support.
- Advancements in AI and ML offer potential solutions for SAH patient care.
Purpose of the Study:
- To review the current state of AI and ML applications in SAH management.
- To identify future directions for AI/ML in SAH patient care.
Main Methods:
- Systematic review of scientific literature.
- Databases searched include Cochrane, MEDLINE, Scopus, and Embase.
- Analysis of 507 identified articles, with 21 deemed relevant.
Main Results:
- AI/ML aids in mortality prediction (e.g., Glasgow Coma Scale, biomarkers).
- Studies show improved prediction of complications and reduced intervention latency.
- AI accurately predicts aneurysmal rupture and assists in interventions (e.g., robotic Doppler).
Conclusions:
- AI/ML technologies have significant potential to improve SAH systems-of-care.
- Staying updated with AI/ML developments is crucial for advancing SAH patient interventions.
Keywords:
Aneurysmal subarachnoid hemorrhageArtificial intelligenceMachine learningSubarachnoid hemorrhage
