ESCMID研讨会:医学微生物学诊断中的人工智能和机器学习。

IF 2.7 4区 医学 Q3 IMMUNOLOGY
Mariella Greutmann, Karsten Borgwardt, Sarah Brüningk, Fabian Franzeck, Christian G Giske, Anna G Green, Alejandro Guerrero-López, Margaret Ip, Catherine Jutzeler, Andre Kahles, Michael Krauthammer, Nenad Macesic, Benjamin McFadden, Eline Meijer, Nathan Moore, Jacob Moran-Gilad, Imane Lboukili, Oliver Nolte, Robin Patel, Gerold Schneider, Markus A Seeger, Tavpritesh Sethi, Robert L Skov, Chang Ho Yoon, Belén Rodríguez-Sánchez, Adrian Egli
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引用次数: 0

摘要

人工智能(AI)和机器学习(ML)的快速发展为改变医学微生物学诊断、改进病原体鉴定、抗菌药物敏感性预测和疫情检测提供了巨大潜力。为了应对这些机遇和挑战,ESCMID于2025年6月2日至5日在瑞士苏黎世举办了“医学微生物学诊断中的人工智能和机器学习”研讨会。课程以专家讲座、实践环节和小组讨论为特色,涵盖基础机器学习概念和深度学习架构、数据互操作性、质量控制流程、模型开发和验证策略。讨论的主要应用包括用于抗菌素耐药性检测的全基因组测序、人工智能增强的数字显微镜自动化和基于MALDI-TOF质谱的诊断。参与者获得了基本人工智能工具和平台的实践经验。特别强调了标准化实验室协议、法规遵从性和道德考虑,包括数据治理和患者隐私。小组会议进一步强调了与人工智能基础设施相关的公平、全球差距、可持续性和环境影响等关键问题。研讨会最后强调,有必要进行持续的跨学科合作、继续教育和对公平的人工智能基础设施进行大量投资,以充分发挥人工智能在临床诊断中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ESCMID workshop: Artificial intelligence and machine learning in medical microbiology diagnostics.

Rapid advancements in artificial intelligence (AI) and machine learning (ML) offer significant potential to transform medical microbiology diagnostics, improving pathogen identification, antimicrobial susceptibility prediction and outbreak detection. To address these opportunities and challenges, the ESCMID workshop, "Artificial Intelligence and Machine Learning in Medical Microbiology Diagnostics", was held in Zurich, Switzerland, from June 2-5, 2025. The course featured expert lectures, practical sessions and panel discussions covering foundational ML concepts and deep learning architectures, data interoperability, quality control processes, model development and validation strategies. Key applications discussed included whole-genome sequencing for antimicrobial resistance detection, AI-enhanced digital microscopy automation and MALDI-TOF mass spectrometry-based diagnostics. Participants gained hands-on experience with essential AI tools and platforms. Special emphasis was placed on standardised laboratory protocols, regulatory compliance and ethical considerations, including data governance and patient privacy. Panel sessions further highlighted critical issues of equity, global disparities in AI access, sustainability and environmental impacts related to AI infrastructure. The workshop concluded by underscoring a necessity for ongoing interdisciplinary collaboration, continued education, and substantial investment in equitable AI infrastructure to realise the full potential of AI in clinical diagnostics.

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来源期刊
Microbes and Infection
Microbes and Infection 医学-病毒学
CiteScore
12.60
自引率
1.70%
发文量
90
审稿时长
40 days
期刊介绍: Microbes and Infection publishes 10 peer-reviewed issues per year in all fields of infection and immunity, covering the different levels of host-microbe interactions, and in particular: the molecular biology and cell biology of the crosstalk between hosts (human and model organisms) and microbes (viruses, bacteria, parasites and fungi), including molecular virulence and evasion mechanisms. the immune response to infection, including pathogenesis and host susceptibility. emerging human infectious diseases. systems immunology. molecular epidemiology/genetics of host pathogen interactions. microbiota and host "interactions". vaccine development, including novel strategies and adjuvants. Clinical studies, accounts of clinical trials and biomarker studies in infectious diseases are within the scope of the journal. Microbes and Infection publishes articles on human pathogens or pathogens of model systems. However, articles on other microbes can be published if they contribute to our understanding of basic mechanisms of host-pathogen interactions. Purely descriptive and preliminary studies are discouraged.
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