Dankwa-Mullan Irene, Ndoh Kingsley, Akogo Darlington, Rocha Hermano Alexandre Lima, Juaçaba Sérgio Ferreira
Milken Institute School of Public Health, Department of Health Policy and Management, George Washington University, Washington D.C., USA.
Hurone AI, Seattle, Washington, USA.
Curr Oncol Rep. 2025 Feb;27(2):95-111. doi: 10.1007/s11912-024-01627-1. Epub 2025 Jan 3.
This review aims to evaluate the impact of artificial intelligence (AI) on cancer health equity, specifically investigating whether AI is addressing or widening disparities in cancer outcomes.
Recent studies demonstrate significant advancements in AI, such as deep learning for cancer diagnosis and predictive analytics for personalized treatment, showing potential for improved precision in care. However, concerns persist about the performance of AI tools across diverse populations due to biased training data. Access to AI technologies also remains limited, particularly in low-income and rural settings. AI holds promise for advancing cancer care, but its current application risks exacerbating existing health disparities. To ensure AI benefits all populations, future research must prioritize inclusive datasets, integrate social determinants of health, and develop ethical frameworks. Addressing these challenges is crucial for AI to contribute positively to cancer health equity and guide future research and policy development.
本综述旨在评估人工智能(AI)对癌症健康公平性的影响,特别研究AI是在解决还是扩大癌症治疗结果方面的差距。
近期研究表明AI取得了重大进展,如用于癌症诊断的深度学习和用于个性化治疗的预测分析,显示出提高医疗精准度的潜力。然而,由于训练数据存在偏差,人们对AI工具在不同人群中的表现仍存在担忧。获得AI技术的机会也仍然有限,特别是在低收入和农村地区。AI有望推动癌症治疗,但目前的应用有加剧现有健康差距的风险。为确保AI造福所有人群,未来研究必须优先考虑包容性数据集,纳入健康的社会决定因素,并制定道德框架。应对这些挑战对于AI为癌症健康公平性做出积极贡献以及指导未来研究和政策制定至关重要。