用于癌症研究和临床试验的人工智能生成的合成数据
Jan-Niklas Eckardt1,2, Waldemar Hahn3,4, Arsela Prelaj5
1Department of Internal Medicine I, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany. jan-niklas.eckardt@ukdd.de.
Nature reviews. Cancer
|February 20, 2026
概括
人工智能生成的合成数据在医疗保健研究中表现有前途,特别是在瘤学和血液学方面. 在为数据访问和临床试验提供解决方案的同时,标准化和验证对于可靠的应用至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 生物统计学 生物统计学
背景情况:
- 使用人工智能 (AI) 生成的合成数据越来越多地用于医学研究.
- 它复制真实世界的数据属性,为传统数据集提供了替代方案.
- 在高风险领域,如血液学和瘤学,应用值得注意.
研究的目的:
- 审查合成数据在癌症研究和临床试验中的作用和影响.
- 检查合成数据的潜在好处,局限性和挑战.
- 建议最佳实践,以提高合成数据的质量和实用性.
主要方法:
- 审查当前文献和合成数据在医疗保健中的现实应用.
- 对挑战进行批判性分析,包括标准化,偏见,隐私和质量保证等.
- 制定关于合成数据生成和应用的最佳实践建议.
主要成果:
- 合成数据可以补充或替代现实世界的数据,克服访问障碍,并可能降低临床试验成本.
- 在标准化,评估,偏见缓解,隐私和质量保证方面仍然存在重大挑战.
- 尽管有局限性,合成数据有可能改善数据共享,协作和试验设计.
结论:
- 合成数据是医疗保健研究的一个有前途的工具,但不是通用的解决方案.
- 严格的验证和监督对于其可靠和安全的应用至关重要.
- 在正确实施的情况下,合成数据可以显著推进癌症研究和临床试验方法.
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