Windermere Sonora Andromeda, Shah Siddharth, Hey Grace, McGrath Kyle, Rahman Maryam
Virginia Commonwealth University Medical Center, Department of General Surgery, Richmond, Virginia, USA.
Department of Neurosurgery, RCSM Government Medical College, Kolhapur, Maharashtra, India.
World Neurosurg. 2025 May;197:123809. doi: 10.1016/j.wneu.2025.123809. Epub 2025 Feb 25.
Artificial intelligence (AI) has become an increasingly prominent tool in the field of neurosurgery, revolutionizing various aspects of patient care and surgical practices. AI-powered systems can provide real-time feedback to surgeons, enhancing precision and reducing the risk of complications during surgical procedures. The objective of this study is to review the role of AI in training neurosurgical residents, improving accuracy during surgery, and reducing complications.
The literature search method involved searching PubMed using relevant keywords to identify English literature publications, including full texts, and concerning human subject matter from its inception until May 2024, initially generating 247,747 results. Articles were then screened for topic relevancy by abstract contents. Further articles were retrieved from the sources cited by the initially reviewed articles. A comprehensive review was then performed on various studies, including observational studies, case-control studies, cohort studies, clinical trials, meta-analyses, and reviews by 4 reviewers individually and then collectively.
Studies on AI in neurosurgery reach more than 4000 produced over a decade alone. The majority of studies regarding clinical diagnosis, risk prediction, and intraoperative guidance remain retrospective in nature. In its current form, AI-based paradigm performed inferiorly to neurosurgery residents in test taking.
AI has potential for broad applications in neurosurgery from use as a diagnostic, predictive, intraoperative, or educational tool. Further research is warranted for prospective use of AI-based technology for delivery of neurosurgical care.
人工智能（AI）已成为神经外科领域日益突出的工具，彻底改变了患者护理和手术操作的各个方面。人工智能驱动的系统可以为外科医生提供实时反馈，提高手术精度并降低手术过程中并发症的风险。本研究的目的是回顾人工智能在培训神经外科住院医师、提高手术准确性和减少并发症方面的作用。
文献检索方法包括使用相关关键词在PubMed上搜索，以识别自该数据库建立至2024年5月期间的英文文献出版物，包括全文，且涉及人类主题，最初产生了247,747条结果。然后通过摘要内容筛选文章的主题相关性。从最初审查的文章引用的来源中检索更多文章。然后由4名审稿人分别对各种研究进行全面审查，包括观察性研究、病例对照研究、队列研究、临床试验、荟萃分析和综述，之后进行集体审查。
仅在过去十年中，关于神经外科领域人工智能的研究就超过4000项。大多数关于临床诊断、风险预测和术中指导的研究本质上仍然是回顾性的。以其目前的形式，基于人工智能的范式在测试中表现不如神经外科住院医师。
人工智能在神经外科领域有广泛的应用潜力，可作为诊断、预测、术中或教育工具。有必要进一步研究基于人工智能的技术在神经外科护理中的前瞻性应用。
