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
{"title":"ESCMID研讨会:医学微生物学诊断中的人工智能和机器学习。","authors":"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","doi":"10.1016/j.micinf.2025.105562","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18497,"journal":{"name":"Microbes and Infection","volume":" ","pages":"105562"},"PeriodicalIF":2.7000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ESCMID workshop: Artificial intelligence and machine learning in medical microbiology diagnostics.\",\"authors\":\"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\",\"doi\":\"10.1016/j.micinf.2025.105562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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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.
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.