Evidence map›Paper›PMID 40145748›Full record

ArticleJournal of clinical microbiology2025

Proceedings of the Clinical Microbiology Open 2024: artificial intelligence applications in clinical microbiology.

Jennifer Dien Bard, Andrea M Prinzi, Paige M K Larkin, David R Peaper, Daniel D Rhoads

Abstract readConference Proceedings
In one paragraph

Article in Journal of clinical microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. [Advances in the Application of Artificial Intelligence in Clinical Microbiological Testing].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
    Review
  5. Review
  6. Artificial intelligence in clinical microbiology: results from the first National survey by the Italian association of clinical microbiologists.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  7. Review
  8. Article
  9. Review
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jennifer Dien Bard *Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles; Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0003-0524-9473
Andrea M Prinzi *US Medical Affairs, bioMérieux, Salt Lake City, USA.ORCID 0000-0003-2949-5484
Paige M K LarkinAmerican Society for Microbiology, Washington, District of Columbia, USA.
David R PeaperDepartment of Laboratory Medicine, Yale University, New Haven, Connecticut, USA.ORCID 0000-0002-9952-5012
Daniel D RhoadsDepartment of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, USA.ORCID 0000-0002-7636-5191

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Clinical Microbiology Open (CMO) is a meeting sponsored by the American Society for Microbiology (ASM) in collaboration with its Corporate Council and Clinical and Public Health Microbiology representatives, which is held to discuss topics that are relevant to both industry and practicing clinical microbiologists. The 2024 CMO was held in Oceanside, California on February 1 and 2. Participants included clinical and public health laboratory directors, representatives from government agencies, and biotechnology industry partners. The group engaged in discussions with the theme, "The Lab of the Future." One of the primary topics discussed was artificial intelligence (AI) opportunities in clinical microbiology laboratories. This report summarizes the discussion and sentiment of the group regarding AI tools, opportunities and challenges of AI in clinical laboratories, and potential future directions for AI in clinical microbiology practice.

Indexed as

Artificial IntelligenceMicrobiological TechniquesMicrobiologyHumansLaboratories, Clinicalartificial intelligenceclinical microbiologyimage analysismachine learning

Identifiers

PMID40145748
PMCPMC11980357

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.