慢性肺部疾病的数字双胞胎.
Apolline Gonsard1, Martin Genet2,3, David Drummond4,5
1Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France.
概括
数字双胞胎提供实时呼吸系统健康可视化和个性化医疗. 本综述探讨了它们在呼吸系统医学中的潜力,以改善患者的治疗结果和疾病的理解.
科学领域:
- 数字健康数字健康
- 网络物理系统 网络物理系统
- 计算建模计算建模
背景情况:
- 数字双胞胎整合了网络物理系统,建模和计算,以实现双向数据流.
- 人工智能和互联设备的进步使实时的患者呼吸系统健康可视化成为可能.
- 复杂的呼吸系统建模支持预测性治疗疗效评估.
研究的目的:
- 审查医疗保健中的数字双胞胎概念.
- 探索数字双胞胎在呼吸系统医学中的可行性和潜在益处.
- 确定与在临床实践中实施数字双胞胎相关的挑战.
主要方法:
- 关于数字双胞胎和呼吸系统医学的当前文献的综述.
- 对技术进步的分析,使得数字双胞胎的创造成为可能.
- 讨论潜在的应用和实施障碍.
主要成果:
- 数字双胞胎可以提供呼吸系统健康的实时可视化.
- 它们具有预测治疗反应和促进个性化医疗的潜力.
- 研究人员可以利用数字双胞胎来研究慢性呼吸道疾病中的基因-环境-时间相互作用.
结论:
- 数字双胞胎为个性化和及时的呼吸护理提供了一个有希望的途径.
- 它们的实施可以提高疾病的理解,早期检测和治疗适应.
- 应对实施挑战对于实现呼吸系统医学中数字双胞胎的全部潜力至关重要.
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