Applications of Artificial Intelligence in Neurosurgery for Improving Outcomes Through Diagnostics, Predictive Tools, and Resident Education
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) shows promise in neurosurgery for training and improving surgical outcomes. However, current AI systems perform below neurosurgery residents in testing, indicating a need for further development.
Area Of Science
- Neurosurgery
- Artificial Intelligence
- Medical Technology
Background
- Artificial intelligence (AI) is increasingly utilized in neurosurgery, enhancing patient care and surgical precision.
- AI systems offer real-time feedback to surgeons, potentially reducing complications.
- The integration of AI in neurosurgery is transforming surgical practices and patient management.
Purpose Of The Study
- To review the application of AI in training neurosurgical residents.
- To assess AI's role in improving surgical accuracy.
- To evaluate AI's impact on reducing surgical complications.
Main Methods
- A comprehensive literature search was conducted on PubMed, yielding 247,747 initial results until May 2024.
- Articles were screened for relevance, and additional sources were identified from cited references.
- A systematic review of diverse study types (observational, trials, reviews) was performed by four independent reviewers.
Main Results
- Over 4000 studies on AI in neurosurgery have been published in the last decade.
- Most current AI research in neurosurgery focuses on retrospective data for diagnosis, risk prediction, and intraoperative guidance.
- AI-based systems currently underperform neurosurgery residents in standardized testing scenarios.
Conclusions
- AI demonstrates significant potential across various neurosurgical applications, including diagnostics, prediction, intraoperative assistance, and education.
- Further prospective research is essential to validate and optimize AI-based technologies for neurosurgical care delivery.
- The findings highlight the need for continued investigation into AI's efficacy and integration into neurosurgical training and practice.
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