人工智能在肿瘤学中的应用与局限性。
Uses and limitations of artificial intelligence for oncology.
机构信息
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA.
出版信息
Cancer. 2024 Jun 15;130(12):2101-2107. doi: 10.1002/cncr.35307. Epub 2024 Mar 30.
Abstract
Modern artificial intelligence (AI) tools built on high-dimensional patient data are reshaping oncology care, helping to improve goal-concordant care, decrease cancer mortality rates, and increase workflow efficiency and scope of care. However, data-related concerns and human biases that seep into algorithms during development and post-deployment phases affect performance in real-world settings, limiting the utility and safety of AI technology in oncology clinics. To this end, the authors review the current potential and limitations of predictive AI for cancer diagnosis and prognostication as well as of generative AI, specifically modern chatbots, which interfaces with patients and clinicians. They conclude the review with a discussion on ongoing challenges and regulatory opportunities in the field.
摘要
现代人工智能 (AI) 工具基于高维患者数据构建，正在重塑肿瘤学护理，有助于提高目标一致的护理水平、降低癌症死亡率，并提高工作流程效率和护理范围。然而，在开发和部署阶段，数据相关的问题和渗透到算法中的人为偏见会影响实际环境中的性能，限制人工智能技术在肿瘤学临床中的实用性和安全性。为此，作者回顾了预测性 AI 在癌症诊断和预后方面的当前潜力和局限性，以及生成性 AI（特别是现代聊天机器人）与患者和临床医生交互的作用。他们在综述的最后讨论了该领域正在面临的挑战和监管机遇。
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