人工智能在肿瘤诊疗研究中的应用

doi:10.3969/j.issn.1006-7795.2025.03.001

摘要/Abstract

摘要： 癌症作为全球主要公共卫生问题，其发病率和病死率持续攀升，对人类健康和社会经济构成了沉重负担。尽管近年来肿瘤研究取得显著进展，但肿瘤的异质性、耐药性以及早期筛查和诊疗技术的局限性仍然是亟待解决的核心挑战。在此背景下，人工智能技术凭借其在大数据分析、模式识别和预测建模方面的独特优势，为肿瘤研究开辟了新的路径。通过整合组学、影像及临床等多模态数据，人工智能不仅加速了肿瘤基础机制的研究，还在早期筛查、生物标志物发现及个性化治疗等领域展现了广阔的应用前景，促进了精准医学与肿瘤学的深度融合。本文全面综述了近年来人工智能技术在肿瘤诊疗研究中的应用进展，重点探讨其在多种数据类型及诊疗场景中的实际价值与未来发展方向。

关键词: 人工智能, 精准医疗, 医疗大数据, 肿瘤研究, 肿瘤诊疗

Abstract: As a major global public health concern, cancer has witnessed a continues rise in both incidence and mortality rates. It pose not only a severe threat to human health but also a heavy burden on socioeconomic systems. Despite remarkable advancements in oncology research, critical challenges such as tumor heterogeneity, drug resistance, and limitations in early screening and diagnostic technologies remain to be addressed. Against this backdrop, artificial intelligence (AI), with its unique advantages in big data analysis, pattern recognition, and predictive modeling, has opened new avenues for cancer research. By integrating multi-modal data, including omics, imaging, and clinical information, AI not only accelerates investigations into fundamental tumor mechanisms but also demonstrates immense potential in areas such as early screening, biomarker discovery, and personalized treatment. These advancements have fostered a deeper integration of precision medicine and oncology. This review provides a comprehensive overview of the most recent progresses in the application of AI in cancer diagnosis and treatment research, with a focus on its practical value across diverse data types and clinical scenarios, as well as future directions for its development.

Key words: artificial intelligence, precision medicine, medical big data, cancer research, oncology diagnostics and therapeutics

中图分类号:

刘红蕾, 杨迎亮, 李荣浩, 朱丛敏, 张旭. 人工智能在肿瘤诊疗研究中的应用[J]. 首都医科大学学报, 2025, 46(3): 395-400.

Liu Honglei, Yang Yingliang, Li Ronghao, Zhu Congmin, Zhang Xu. Application of artificial intelligence in the study of cancer diagnosis and treatment research[J]. Journal of Capital Medical University, 2025, 46(3): 395-400.

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