人工智能在传染病诊断技术中的应用
Chao Dong1, Yujing Liu1, Jiaqi Nie1
1Hebei Key Laboratory of Analysis and Control of Zoonotic Pathogenic Microorganism, College of Life Sciences, Hebei Agricultural University, Baoding 071001, China.
Diagnostics (Basel, Switzerland)
|October 29, 2025
概括
人工智能 (AI) 通过先进的数据分析和模式识别显著提高了传染病诊断. 本综述综合了人工智能应用,强调了病原体监测和早期疫情检测的好处,同时指出了实施的挑战.
科学领域:
- 传染病医学 传染病医学
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 人工智能 (AI) 正在迅速融入传染病医学,为复杂的健康挑战提供新的方法.
- 流行病,新兴传染病和抗菌素耐药性等全球威胁需要先进的诊断工具.
- 人工智能在数据挖掘,模式识别和预测分析方面的能力对于改善诊断结果至关重要.
研究的目的:
- 系统地审查和综合当前AI应用在传染病诊断中的现状.
- 检查人工智能在诸如病原体监测和成像分析等领域的技术进步和实际成果.
- 批判性地分析阻碍基于AI的诊断技术临床转化所面临的挑战和局限性.
主要方法:
- 在PubMed和Web of Science数据库中的系统文献搜索.
- 包括在2018年至2025年期间发表的研究,重点关注在传染病诊断中的AI.
- 叙事审查综合了人工智能应用,技术进步和临床翻译障碍的发现.
主要成果:
- 人工智能在诊断援助方面展示了变革性的潜力,提高了效率和准确性.
- 关键应用包括用于病原体监测的高通量测序 (HTS),数字/放射图像的AI分析,以及AI增强的临床检测 (POCT).
- 重要挑战包括数据稀缺,模型通用性问题,经济负担和监管障碍.
结论:
- 人工智能通过增强的诊断提供了针对流行病控制,新兴疾病和抗菌素耐药性的创新解决方案.
- 克服数据,概括性,经济和监管方面的挑战对于广泛的临床采用至关重要.
- 本综述为未来开发,验证和标准化人工智能辅助传染病诊断的研究提供了框架.
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