欧洲医疗微生物发展中心 (ESCMID) 研讨会:医疗微生物学诊断中的人工智能和机器学习
Mariella Greutmann1, Karsten Borgwardt2, Sarah Brüningk3
1Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland.
Microbes and infection
|September 7, 2025
概括
人工智能 (AI) 和机器学习 (ML) 可以彻底改变医学微生物学诊断. 在ESCMID研讨会上强调了需要合作,教育和投资,以确保在临床环境中公平地实施人工智能.
科学领域:
- 医学微生物学 医学微生物学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 人工智能和机器学习领域的快速发展为医学微生物学诊断提供了机会.
- 挑战包括数据互操作性,质量控制和道德考虑.
研究的目的:
- 探索AI和ML在医学微生物学诊断中的应用.
- 应对挑战,促进现场合作.
主要方法:
- 专家讲座和AI/ML概念和应用的实践课程.
- 关于监管合规,道德,公平和可持续性的小组讨论.
- 与人工智能工具和平台的实践经验.
主要成果:
- 讨论的主要应用:针对抗菌素耐药性的全基因组测序,AI增强的数字显微镜和MALDI-TOF MS诊断.
- 强调标准化的协议,监管合规和道德考虑.
- 确定了关键问题:公平,全球差距,可持续性和环境影响.
结论:
- 人工智能和机器学习具有改善病原体识别,抗菌素易感性预测和疫情检测的巨大潜力.
- 跨学科的合作,持续教育和对公平的人工智能基础设施的投资至关重要.
- 实现人工智能在临床诊断中的全部潜力需要解决伦理和全球差异.
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