传统,补充和整合医学和人工智能:医疗保健中的新机遇
Jeremy Y Ng1,2,3, Holger Cramer2,3, Myeong Soo Lee4
1Centre for Journalology, Ottawa Hospital Research Institute, Ottawa, Canada.
Integrative medicine research
|February 22, 2024
概括
人工智能 (AI) 可以通过个性化治疗和改善患者护理来增强传统,补充和整合医学 (TCIM). 解决数据隐私和偏见等挑战对于成功的集成至关重要.
科学领域:
- 综合医学是一个整体的医学.
- 医疗保健中的人工智能
- 数字健康数字健康
背景情况:
- 传统,补充和整合医学 (TCIM) 提供以患者为中心的整体健康方法.
- 人工智能 (AI) 为数据驱动的决策和个性化的医疗保健提供了机会.
- TCIM和AI的融合旨在改善患者的治疗结果,提高护理质量.
研究的目的:
- 探索人工智能技术如何补充和增强TCIM.
- 确定将AI与TCIM集成的机遇和挑战.
- 调整研究目标,以改善患者的治疗结果和整体健康.
主要方法:
- 对医疗保健中人工智能应用的当前文献的综述.
- 对人工智能增强TCIM实践潜力的分析.
- 在AI和TCIM的交叉点上确定挑战和伦理考虑.
主要成果:
- 人工智能可以协助早期疾病检测,个性化治疗计划,健康趋势预测和TCIM中的患者参与.
- 关键的挑战包括数据隐私,监管障碍,在护理中保持人类因素以及减轻AI偏见.
- 患者的信任,知情同意和问责制对于人工智能驱动的TCIM至关重要.
结论:
- 人工智能和TCIM的整合为彻底改变医疗保健提供提供提供了重大前景.
- 解决伦理,监管和实际挑战对于成功实施至关重要.
- 未来的研究应该集中在缓解偏见,患者接受和理解人工智能对患者提供者互动的影响上.
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