Kuperberg Stephen J, Christiani David C
Division of Pulmonary and Critical Care Medicine, New York City Health and Hospitals, Woodhull Brooklyn New York USA.
New York University Grossman School of Medicine New York New York USA.
Cancer Innov. 2025 Jun 20;4(4):e70019. doi: 10.1002/cai2.70019. eCollection 2025 Aug.
Although lung cancer remains a global threat to public health, evidenced based advances in screening and prevention hold promise for reducing its impact on mortality. An ongoing challenge facing the clinical and research community are the glaring disparities in access to preventive services faced by ethnically and socioeconomically marginalized groups. In this context, novel approaches are needed to improve research methods and thus bolster our ability to improve outcomes. Artificial intelligence (AI) applications such as machine learning and natural language processing hold promise as catalysts in this process, enhancing speed, accuracy and capability. This perspective will highlight the potential of AI methods as essential tool for growth across the lung cancer diagnostic continuum from screening to diagnosis.
尽管肺癌仍然是对全球公共卫生的一大威胁,但基于证据的筛查和预防进展有望降低其对死亡率的影响。临床和研究界面临的一个持续挑战是,在获得预防服务方面,种族和社会经济边缘化群体存在明显差异。在这种背景下,需要新的方法来改进研究方法,从而增强我们改善结果的能力。机器学习和自然语言处理等人工智能(AI)应用有望成为这一过程中的催化剂,提高速度、准确性和能力。这一观点将强调人工智能方法作为从筛查到诊断的肺癌诊断连续过程中促进发展的重要工具的潜力。