ArticleAntimicrobial agents and chemotherapy2021
Analysis of Multidrug Resistance in Staphylococcus aureus with a Machine Learning-Generated Antibiogram.
Article in Antimicrobial agents and chemotherapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 21 citations in OpenAlex.
- Analyzing multidrug resistance patterns across the food supply chain using association rule mining.Preventive veterinary medicine · 2026Article
- Exploring multidrug resistance patterns in community-acquiredAntimicrobial agents and chemotherapy · 2025Article
- Exploring the evolution of multidrug resistance patterns in ESKAPEE pathogens using association mining: Key to antibiotic stewardship?Wellcome open research · 2025Article
- A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria.Frontiers in antibiotics · 2024Article
- Prediction of antimicrobial resistance of Klebsiella pneumoniae from genomic data through machine learning.PloS one · 2024Article
- Comparative De Novo and Pan-Genome Analysis of MDR Nosocomial Bacteria Isolated from Hospitals in Jeddah, Saudi Arabia.Microorganisms · 2023Article
- Using Machine Learning to Predict Antimicrobial Resistance-A Literature Review.Antibiotics (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Multidrug resistance (MDR) surveillance consists of reporting MDR prevalence and MDR phenotypes. Detailed knowledge of the specific associations underlying MDR patterns can allow antimicrobial stewardship programs to accurately identify clinically relevant resistance patterns. We applied machine learning and graphical networks to quantify and visualize associations between resistance traits in a set of 1,091
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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.