Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Rotman Institute of Philosophy, Western University, London, ON, Canada.
J Med Internet Res. 2022 Nov 1;24(11):e39748. doi: 10.2196/39748.
The field of oncology is at the forefront of advances in artificial intelligence (AI) in health care, providing an opportunity to examine the early integration of these technologies in clinical research and patient care. Hope that AI will revolutionize health care delivery and improve clinical outcomes has been accompanied by concerns about the impact of these technologies on health equity.
We aimed to conduct a scoping review of the literature to address the question, "What are the current and potential impacts of AI technologies on health equity in oncology?"
Following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines for scoping reviews, we systematically searched MEDLINE and Embase electronic databases from January 2000 to August 2021 for records engaging with key concepts of AI, health equity, and oncology. We included all English-language articles that engaged with the 3 key concepts. Articles were analyzed qualitatively for themes pertaining to the influence of AI on health equity in oncology.
Of the 14,011 records, 133 (0.95%) identified from our review were included. We identified 3 general themes in the literature: the use of AI to reduce health care disparities (58/133, 43.6%), concerns surrounding AI technologies and bias (16/133, 12.1%), and the use of AI to examine biological and social determinants of health (55/133, 41.4%). A total of 3% (4/133) of articles focused on many of these themes.
Our scoping review revealed 3 main themes on the impact of AI on health equity in oncology, which relate to AI's ability to help address health disparities, its potential to mitigate or exacerbate bias, and its capability to help elucidate determinants of health. Gaps in the literature included a lack of discussion of ethical challenges with the application of AI technologies in low- and middle-income countries, lack of discussion of problems of bias in AI algorithms, and a lack of justification for the use of AI technologies over traditional statistical methods to address specific research questions in oncology. Our review highlights a need to address these gaps to ensure a more equitable integration of AI in cancer research and clinical practice. The limitations of our study include its exploratory nature, its focus on oncology as opposed to all health care sectors, and its analysis of solely English-language articles.
肿瘤学领域处于医疗保健中人工智能（AI）发展的前沿，为检验这些技术在临床研究和患者护理中的早期整合提供了机会。人们希望 AI 将彻底改变医疗保健的提供方式并改善临床结果，但同时也对这些技术对健康公平性的影响表示担忧。
我们旨在对文献进行综述，以回答以下问题：“AI 技术对肿瘤学中的健康公平性有哪些当前和潜在的影响？”
根据 PRISMA-ScR（系统评价和荟萃分析扩展的首选报告项目用于范围综述）指南，我们系统地检索了 MEDLINE 和 Embase 电子数据库，以获取自 2000 年 1 月至 2021 年 8 月期间与 AI、健康公平性和肿瘤学的关键概念相关的记录。我们纳入了所有与这 3 个关键概念相关的英文文章。对与 AI 对肿瘤学中健康公平性的影响相关的主题进行了定性分析。
在我们的综述中，从 14011 条记录中确定了 133 篇（0.95%）文章符合纳入标准。我们在文献中发现了 3 个一般主题：使用 AI 减少医疗保健差距（58/133，43.6%）、对 AI 技术和偏见的担忧（16/133，12.1%）和使用 AI 来检查健康的生物和社会决定因素（55/133，41.4%）。共有 3%（4/133）的文章重点关注了其中的多个主题。
我们的范围综述揭示了 AI 对肿瘤学中健康公平性的影响的 3 个主要主题，这些主题与 AI 帮助解决健康差异的能力、其减轻或加剧偏见的潜力以及帮助阐明健康决定因素的能力有关。文献中的空白包括缺乏对 AI 技术在低收入和中等收入国家应用的伦理挑战的讨论、缺乏对 AI 算法中偏见问题的讨论以及缺乏对 AI 技术的使用进行论证，以解决肿瘤学中特定研究问题的合理性，而不是使用传统的统计方法。我们的综述强调需要解决这些差距，以确保更公平地将 AI 整合到癌症研究和临床实践中。本研究的局限性包括其探索性性质、侧重于肿瘤学而不是所有医疗保健部门以及仅分析英文文章。
