通过人工智能在重症监护脏病学方面的进展
Wisit Cheungpasitporn1, Charat Thongprayoon2, Kianoush B Kashani1,3
1Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester.
Current opinion in critical care
|September 9, 2024
概括
人工智能 (AI),包括机器学习 (ML) 和大型语言模型 (LLM),正在改变关键护理科. 这些技术有望增强急性损伤 (AKI) 检测,预测和个性化治疗,改善患者的治疗结果.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 人工智能的人工智能
- 关键护理医学 关键护理医学
背景情况:
- 关键护理脏学在治疗急性损伤 (AKI) 方面面临着挑战.
- 人工智能 (AI) 的进步,特别是机器学习 (ML) 和大型语言模型 (LLM),提供了新的解决方案.
研究的目的:
- 审查人工智能在重症监护脏病学中的进展,应用和影响.
- 探索ML和LLMs在管理AKI和连续脏替代疗法的潜力.
主要方法:
- 对人工智能在重症监护脏病学中的应用进行文献综述.
- 在AKI检测,预测和治疗个性化方面分析ML和LLM能力.
主要成果:
- 人工智能算法增强了早期AKI检测和风险预测,提前24-48小时识别患者.
- 机器学习模型可以识别针对性干预的AKI亚现象型.
- 法律职责管理工具促进了自动化临床笔记和患者教育,提高了理解和参与度.
结论:
- 人工智能在重症监护脏病学中的整合有可能彻底改变AKI管理.
- 成功实施人工智能需要解决数据质量,道德问题和验证问题.
- 持续的培训和合作对于临床医生有效采用人工智能至关重要.
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