大数据,机器学习和医疗系统中的个性化:伦理问题和新兴的权衡
Stefano Canali1, Alessandro Falcetta2, Massimo Pavan2
1Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy. stefano.canali@polimi.it.
Science and engineering ethics
|October 13, 2025
概括
医疗系统中的大数据和机器学习提供了个性化,但也引发了伦理方面的担忧. 个性化的葡萄糖监测模型揭示了权衡,显示个性化并不总是有益的.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 大数据和机器学习 (ML) 在医疗系统中越来越多地被使用.
- 伦理问题和社会影响被广泛讨论.
- 医疗保健中的个性化具有显著的前景.
研究的目的:
- 检查大数据和机器学习在卫生系统中的个性化应用.
- 识别与个性化健康模型相关的挑战和权衡.
- 评估个性化是否总是医疗保健的积极发展.
主要方法:
- 专注于个性化模型的具体应用.
- 对葡萄糖监测个性化模型的分析.
- 分析个性化模型用于异常检测.
主要成果:
- 个性化模型可以引入新的和加剧的问题.
- 在卫生系统中个性化并非普遍有益.
- 确定了个性化优势与新出现的问题之间的权衡.
结论:
- 在卫生系统中追求个性化需要仔细考虑其缺点.
- 从个性化大数据和机器学习应用中出现了新的伦理问题.
- 需要采取缓解策略来应对个性化健康模型带来的挑战.
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