Tangsrivimol Jonathan A, Schonfeld Ethan, Zhang Michael, Veeravagu Anand, Smith Timothy R, Härtl Roger, Lawton Michael T, El-Sherbini Adham H, Prevedello Daniel M, Glicksberg Benjamin S, Krittanawong Chayakrit
Division of Neurosurgery, Department of Surgery, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok 10210, Thailand.
Department of Neurological Surgery, The Ohio State University Wexner Medical Center and Jame Cancer Institute, Columbus, OH 43210, USA.
Diagnostics (Basel). 2023 Jul 20;13(14):2429. doi: 10.3390/diagnostics13142429.
In recent years, there has been a significant surge in discussions surrounding artificial intelligence (AI), along with a corresponding increase in its practical applications in various facets of everyday life, including the medical industry. Notably, even in the highly specialized realm of neurosurgery, AI has been utilized for differential diagnosis, pre-operative evaluation, and improving surgical precision. Many of these applications have begun to mitigate risks of intraoperative and postoperative complications and post-operative care. This article aims to present an overview of the principal published papers on the significant themes of tumor, spine, epilepsy, and vascular issues, wherein AI has been applied to assess its potential applications within neurosurgery. The method involved identifying high-cited seminal papers using PubMed and Google Scholar, conducting a comprehensive review of various study types, and summarizing machine learning applications to enhance understanding among clinicians for future utilization. Recent studies demonstrate that machine learning (ML) holds significant potential in neuro-oncological care, spine surgery, epilepsy management, and other neurosurgical applications. ML techniques have proven effective in tumor identification, surgical outcomes prediction, seizure outcome prediction, aneurysm prediction, and more, highlighting its broad impact and potential in improving patient management and outcomes in neurosurgery. This review will encompass the current state of research, as well as predictions for the future of AI within neurosurgery.
近年来，围绕人工智能（AI）的讨论显著增多，其在包括医疗行业在内的日常生活各个方面的实际应用也相应增加。值得注意的是，即使在神经外科这一高度专业化的领域，人工智能也已被用于鉴别诊断、术前评估以及提高手术精度。其中许多应用已开始降低术中及术后并发症和术后护理的风险。本文旨在概述已发表的关于肿瘤、脊柱、癫痫和血管问题等重要主题的主要论文，其中人工智能已被应用于评估其在神经外科中的潜在应用。该方法包括使用PubMed和谷歌学术搜索高被引的开创性论文，对各种研究类型进行全面综述，并总结机器学习应用，以增强临床医生对其的理解以便未来使用。近期研究表明，机器学习（ML）在神经肿瘤护理、脊柱手术、癫痫管理及其他神经外科应用中具有巨大潜力。ML技术已在肿瘤识别、手术结果预测、癫痫发作结果预测、动脉瘤预测等方面证明有效，凸显了其在改善神经外科患者管理和治疗结果方面的广泛影响和潜力。本综述将涵盖当前的研究现状以及对神经外科领域人工智能未来的预测。
