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Published on: August 24, 2011
Artificial Intelligence in Intracerebral Hemorrhage: Current Applications and Future Perspectives
Xinghua Xu1, Jiashu Zhang1, Zhichao Gan1
1Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
Journal of Clinical Medicine
|July 28, 2026
Summary
Artificial intelligence (AI) shows promise in improving diagnosis and management for intracerebral hemorrhage (ICH) patients. AI models enhance accuracy in imaging analysis and outcome prediction, paving the way for data-driven precision neurosurgical care.
Area of Science:
- Neurosurgery
- Medical Imaging
- Artificial Intelligence
Background:
- Intracerebral hemorrhage (ICH) is a severe stroke type with high mortality and poor outcomes.
- Current ICH management faces challenges due to disease heterogeneity and lack of personalized treatments.
Purpose of the Study:
- To review the applications, limitations, and future directions of artificial intelligence (AI) in intracerebral hemorrhage (ICH) management.
- To explore AI's potential in improving diagnosis, prognosis, and precision care for ICH.
Main Methods:
- Systematic literature search in PubMed, Web of Science, and Embase.
- Inclusion criteria focused on AI applications in ICH imaging, prognosis, decision support, and surgery.
- Review and synthesis of identified studies on AI in ICH.
Main Results:
- AI models significantly improve accuracy in hematoma segmentation and expansion prediction.
- AI enhances functional outcome prognostication compared to conventional methods.
- AI applications include multimodal foundation models, intelligent surgical assistance, and personalized care.
Conclusions:
- AI has the potential to revolutionize ICH management towards data-driven, personalized precision care.
- Barriers to clinical translation include data heterogeneity, validation, interpretability, and workflow integration.
- Further development and validation are needed for widespread AI adoption in ICH.
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