人工智能和传染病:范围和前景
S Abbara1, Y Crabol2, J Goupil de Bouillé3
1Infectious Disease Department, R. Poincaré, University Hospital, APHP, Paris, France; Versailles Saint Quentin University, Versailles, France; Groupe Infectiologie Digitale-SPILF, Paris, France.
Infectious diseases now
|August 4, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在改变传染病护理,提高诊断,预后和药物发现. 人工智能实施的挑战需要严格的评估,以确保安全和公平的采用.
科学领域:
- 传染性疾病 传染性疾病
- 医疗信息学 医疗信息学
- 计算生物学 计算生物学
背景情况:
- 人工智能 (AI) 越来越多地被整合到医疗保健中,特别是在传染病实践中.
- 机器学习 (ML) 模型利用各种应用程序的日常护理和研究数据.
- 大型语言模型 (LLM) 在处理临床叙述和支持决策方面提供了先进的能力.
研究的目的:
- 审查当前在传染病实践中的AI应用.
- 评估人工智能工具的证据优势和局限性.
- 提出与临床和监管需求一致的人工智能采用路线图.
主要方法:
- 在传染病中对人工智能的当前文献的综合.
- 分析人工智能在诊断,预后,抗微生物管理和药物发现方面的应用.
- 确定现实世界AI部署的挑战和要求.
主要成果:
- 人工智能增强了传染病诊断 (例如,图像分析,病原体识别) 和预后 (例如,预测临床恶化).
- 机器学习模型改善了抗微生物药物管理,加速了药物发现.
- 临床医学转化临床数据,协助队列生成,并提供临床决策支持.
- 部署的挑战包括成本,实施限制,模型可转移性和风险治理.
结论:
- 人工智能为彻底改变传染病管理提供了巨大的潜力.
- 解决实施障碍和建立强大的评估框架对于安全有效的AI采用至关重要.
- 需要一个翻译路线图,以将技术创新与临床和监管现实联系起来.
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