脑肿瘤患者的病程和临床结果不仅取决于肿瘤的分子和组织学特征，还取决于患者的人口统计学和健康的社会决定因素。虽然目前神经肿瘤学的研究已广泛利用人工智能（AI）来丰富肿瘤诊断并更准确地预测治疗反应、术后并发症和生存率，但公平驱动的人工智能应用仍然受到限制。然而，在更广泛的医疗领域促进健康公平的人工智能应用有可能成为解决神经肿瘤护理中已知差异的实用蓝图。在这篇共识综述中，我们将描述人工智能在神经肿瘤学中的当前应用，根据更广泛的文献，为神经肿瘤学中最紧迫的不平等问题提出可行的人工智能解决方案，提出一个将公平有效整合到基于人工智能的神经肿瘤学中的框架。肿瘤学研究，并接近人工智能的局限性。© 作者 2024。由牛津大学出版社代表神经肿瘤学会出版。版权所有。如需商业重复使用，请联系 reprints@oup.com 获取转载和转载的翻译权。所有其他权限均可通过我们网站文章页面上的“权限”链接通过我们的 RightsLink 服务获得 - 如需了解更多信息，请联系journals.permissions@oup.com。

The disease course and clinical outcome for brain tumor patients depend not only on the molecular and histological features of the tumor but also on the patient's demographics and social determinants of health. While current investigations in neuro-oncology have broadly utilized artificial intelligence (AI) to enrich tumor diagnosis and more accurately predict treatment response, postoperative complications, and survival, equity-driven applications of AI have been limited. However, AI applications to advance health equity in the broader medical field have the potential to serve as practical blueprints to address known disparities in neuro-oncologic care. In this consensus review, we will describe current applications of AI in neuro-oncology, postulate viable AI solutions for the most pressing inequities in neuro-oncology based on broader literature, propose a framework for the effective integration of equity into AI-based neuro-oncology research, and close with the limitations of AI.© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.