从经验到智能：人工智能赋能肿瘤症状管理的研究进展

From Experience to Intelligence: Research Progress on Artificial Intelligence-Enabled Cancer Symptom Management

摘要: 全球肿瘤发病率攀升加剧癌症幸存者症状负担与照护需求。人工智能凭借其卓越的数据处理与模式识别能力，正在重塑肿瘤护理的服务范式。本文系统梳理人工智能在肿瘤症状管理中的三大核心应用：精准感知(早期识别与诊断)、智能协同(症状干预与决策支持)及全程守护(院外随访与自我管理)。本文基于最新证据分析各应用场景的技术优势与临床价值并深入探讨算法偏见、数据孤岛、伦理困境等关键挑战，提出未来研究应聚焦于开发可解释性强的算法、构建跨机构数据共享规范及探索“人机协同”的新型护理模式，以期为推动智能护理发展提供理论依据与实践参考。

Abstract: The rising incidence of cancer in the world intensifies the symptom burden and care needs of cancer survivors. With its excellent data processing and pattern recognition capabilities, artificial intelligence is reshaping the service paradigm of cancer care. This paper systematically sorts out the three core applications of artificial intelligence in tumor symptom management: accurate perception (early identification and diagnosis), intelligent collaboration (symptom intervention and decision support) and whole-process guardianship (out-of-hospital follow-up and self-management). Based on the latest evidence, this paper analyzes the technical advantages and clinical value of each application scenario, and deeply discusses the key challenges such as algorithm bias, data island and ethical dilemma. It is proposed that future research should focus on developing interpretable algorithms, constructing inter-institutional data sharing norms and exploring a new nursing model of “man-machine collaboration” in order to provide theoretical basis and practical reference for promoting the development of intelligent nursing.