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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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机器学习和人工智能在纳米医学中的应用.

Wei-Chun Chou1,2, Alexa Canchola1, Fan Zhang3

  • 1Department of Environmental Sciences, University of California, Riverside, California, USA.

Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
|August 14, 2025
PubMed
概括

人工智能 (AI) 和机器学习 (ML) 通过优化纳米粒子设计和预测有效性来加速纳米医学的发展. 数据标准化和临床整合的监管框架仍然存在挑战.

关键词:
人工智能的人工智能是人工智能.药物输送是药物输送的过程.机器学习是机器学习.纳米医药是一种纳米医药.药物动力学 药物动力学

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科学领域:

  • 纳米医学是一种纳米医学.
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 纳米医学利用纳米粒子在各种疾病中提供有针对性的治疗.
  • 纳米医学的临床翻译在优化和预测人类疗效方面面临着挑战.
  • 人工智能 (AI) 和机器学习 (ML) 为开发障碍提供了解决方案.

研究的目的:

  • 审查AI和ML在纳米医学开发中的应用.
  • 突出AI驱动纳米医学的成功和持续的障碍.
  • 提出纳米医学有效临床整合的途径.

主要方法:

  • 用于查,配方合理化和生物分布预测的AI / ML模型.
  • 高通量数据收集技术 (DNA条形码,自动化液体处理).
  • 蛋白质冠状形成的建模及其对纳米粒子行为的影响.

主要成果:

  • 人工智能加速发现,优化纳米粒子设计,减少试错.
  • 人工智能提高了生物分布和蛋白质冠冕效应的预测.
  • 人工智能有助于理解纳米粒子免疫性和细胞吸收.

结论:

  • 人工智能和机器学习是纳米医学中的变革性工具,增强了设计和临床前预测.
  • 数据标准化,模型通用性和监管清晰度对于临床翻译至关重要.
  • 为了实现人工智能驱动的纳米医学集成,需要协调数据,验证和指导方针.