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机器学习方法来预测喘恶化:叙述性审查
Nestor A Molfino1, Gianluca Turcatel2, Daniel Riskin3
1Global Development, Amgen Inc., One Amgen Center Dr, Thousand Oaks, CA, 91320, USA. nmolfino@amgen.com.
人工智能 (AI) 和机器学习 (ML) 可以通过分析各种患者数据来预测喘恶化. 需要进一步的研究来探索AI/ML.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 计算医学是一种计算医学.
- 呼吸系统药物 呼吸系统药物
背景情况:
- 尽管取得了进展,喘管理仍然具有挑战性,许多患者经历了急性恶化.
- 疾病活动受到许多因素的影响,包括病史,环境和患者的习惯.
- 目前的喘治疗方案不能完全预防喘恶化.
研究的目的:
- 审查人工智能 (AI) 和机器学习 (ML) 在喘管理中的当前证据.
- 探索AI和ML在预测喘恶化方面的潜力.
- 确定AI/ML在临床喘护理中的未来应用和挑战.
主要方法:
- 关于喘中的AI和ML现有科学证据的文献综述.
- 分析表明AI/ML对喘恶化的预测能力的研究.
- 综合影响喘恶化的因素,并将其整合到AI/ML模型中.
主要成果:
- 人工智能和机器学习在准确预测喘恶化方面表现有前途.
- 这些技术可以整合广泛的患者特定数据进行全面分析.
- 现有研究突出了当前AI/ML应用的潜力,也突出了其局限性.
结论:
- 人工智能和机器学习提供了一种有前途的方法来彻底改变个性化喘管理.
- 在喘治疗中AI/ML的临床应用仍处于早期阶段.
- 进一步的研究对于克服实施障碍和优化AI/ML用于喘恶化预测至关重要.
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