ArticleJournal of medical microbiology2020
Same-day antimicrobial susceptibility test using acoustic-enhanced flow cytometry visualized with supervised machine learning.
Article in Journal of medical microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled 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.
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
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Systematic review of surveillance systems for AMR in Africa.The Journal of antimicrobial chemotherapy · 2022Pooled it
- Gram differentiation of bacteria by acoustic-enhanced flow cytometry.Journal of medical microbiology · 2026Article
- Artificial Intelligence for Antimicrobial Resistance Detection and Prediction inInfection and drug resistance · 2026Review
- Flow cytometry enables rapid evaluation of novel, new and niche antimicrobial agents.Frontiers in microbiology · 2026Article
- Artificial intelligence-enhanced biosurveillance for antimicrobial resistance in sub-Saharan Africa.International health · 2025Review
- Marginal notes, June 2025. Artificial Stupidity.Journal of medical microbiology · 2025Article
- Detection of antimicrobial resistance via state-of-the-art technologies versus conventional methods.Frontiers in microbiology · 2025Review
- Advancements in AI-driven drug sensitivity testing research.Frontiers in cellular and infection microbiology · 2025Review
- Flow Cytometry as a Rapid and Valuable Method in Investigation of Colistin Resistance in Carbapenem-ResistantAntibiotics (Basel, Switzerland) · 2024Article
- Current and Future Flow Cytometry Applications Contributing to Antimicrobial Resistance Control.Microorganisms · 2023Review
- Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics-Current State and Whole Genome Sequencing Implementation Perspectives.Antibiotics (Basel, Switzerland) · 2023Review
- Artificial Intelligence for Antimicrobial Resistance Prediction: Challenges and Opportunities towards Practical Implementation.Antibiotics (Basel, Switzerland) · 2023Review
- Using Machine Learning to Predict Antimicrobial Resistance-A Literature Review.Antibiotics (Basel, Switzerland) · 2023Review
- Same-day confirmation of infection and antimicrobial susceptibility profiling using flow cytometry.EBioMedicine · 2022Article
- Artificial Intelligence in Infection Management in the ICU.Critical care (London, England) · 2022Review
- Surveillance of antimicrobial resistance in low- and middle-income countries: a scattered picture.Antimicrobial resistance and infection control · 2021Review
- A fast impedance-based antimicrobial susceptibility test.Nature communications · 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
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
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.