ReviewJournal of clinical microbiology2013
Automation in clinical microbiology.
Review in Journal of clinical microbiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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.
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.
Who cites it
54 citing papers in PubMed.
- Evaluation of the BD urine culture application for artificial intelligence-assisted urine culture interpretation.Journal of clinical microbiology · 2026Article
- Deep neural networks in medical microbiology for bacterial colonies classification.Scientific reports · 2026Article
- PRISM: A unified platform for phage isolation and characterization from single-droplet microenvironments.Science advances · 2026Article
- Collaborative Robotics, Mobile Platforms, and Total Laboratory Automation in Clinical Diagnostics.Diagnostics (Basel, Switzerland) · 2026Review
- Total Laboratory Automation for Microbiology Activities: An HTA Analysis in an Italian Laboratory Setting.ClinicoEconomics and outcomes research : CEOR · 2026Article
- Evolving microbiology laboratories: mastering automated culture-based processes and molecular assays, an institutional experience.Frontiers in cellular and infection microbiology · 2026Review
- Evaluation of automated streaking patterns in urine culture for clinical workflow optimization.Scientific reports · 2025Article
- A digital plating platform for robust and versatile microbial detection and analysis.Scientific reports · 2025Article
- Virtual Gram staining of label-free bacteria using dark-field microscopy and deep learning.Science advances · 2025Article
- Conversion of a classical microbiology laboratory to a total automation laboratory enhanced by the application of lean principles.Microbiology spectrum · 2024Article
- Performance of the VITEK® MS system for the identification of filamentous fungi in a microbiological laboratory in Chile.PloS one · 2024Article
- Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology.Nature communications · 2023Article
- Clinical microbiology in detection and identification of emerging microbial pathogens: past, present and future.Emerging microbes & infections · 2022Article
- Total Laboratory Automation for Rapid Detection and Identification of Microorganisms and Their Antimicrobial Resistance Profiles.Frontiers in cellular and infection microbiology · 2022Review
- Digital imaging for reading of direct rapid antibiotic susceptibility tests from positive blood cultures.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021Article
- Effects of Automation on Sustainability of Immunohistochemistry Laboratory.Healthcare (Basel, Switzerland) · 2021Article
- Scanning Electron Microscope: A New Potential Tool to Replace Gram Staining for Microbe Identification in Blood Cultures.Microorganisms · 2021Article
- Laboratory Automation in the Microbiology Laboratory: an Ongoing Journey, Not a Tale?Journal of clinical microbiology · 2021Article
- Flow-based System: A Highly Efficient Tool Speeds Up Data Production and Improves Analytical Performance.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2021Article
- Deep Learning Frameworks for Rapid Gram Stain Image Data Interpretation: Protocol for a Retrospective Data Analysis.JMIR research protocols · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Historically, the trend toward automation in clinical pathology laboratories has largely bypassed the clinical microbiology laboratory. In this article, we review the historical impediments to automation in the microbiology laboratory and offer insight into the reasons why we believe that we are on the cusp of a dramatic change that will sweep a wave of automation into clinical microbiology laboratories. We review the currently available specimen-processing instruments as well as the total laboratory automation solutions. Lastly, we outline the types of studies that will need to be performed to fully assess the benefits of automation in microbiology laboratories.
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Registered trials
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.