Dataset of microscopy images of untreated and treated E.coli lab strains and clinical isolates, and machine learning models trained on them. Corresponding publications: https://doi.org/10.1101/2022.12.08.22283219 Corresponding analysis code: https://github.com/KapanidisLab/Deep-Learning-and-Single-Cell-Phenotyping-for-Rapid-Antimicrobial-Susceptibility-Testin
In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies...
The model files and data sets are related to publications of: 1) the research article "Li, C., Suth...
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless a...
Training and test images of E. coli cells treated with different antibiotics for antibiotic phenotyp...
Antimicrobial Resistance (AMR) is a growing concern in the medical field. Over-prescription of antib...
Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, but its ...
Resistant microorganisms are causing more and more problems in healthcare. Number of antibiotic-resi...
This record contains the checkpoint for a Chemprop model trained to predict the probability that a m...
Timely determination of antimicrobial susceptibility for a bacterial infection enables precision pre...
<div><p>Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, ...
The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, th...
Antibiotic resistance is an imminent threat to global health. Patient treatment regimens are often s...
Training and test images of live, membrane-labeled E. coli cells for prediction of SIM super-resolut...
The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, th...
The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, th...
In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies...
The model files and data sets are related to publications of: 1) the research article "Li, C., Suth...
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless a...
Training and test images of E. coli cells treated with different antibiotics for antibiotic phenotyp...
Antimicrobial Resistance (AMR) is a growing concern in the medical field. Over-prescription of antib...
Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, but its ...
Resistant microorganisms are causing more and more problems in healthcare. Number of antibiotic-resi...
This record contains the checkpoint for a Chemprop model trained to predict the probability that a m...
Timely determination of antimicrobial susceptibility for a bacterial infection enables precision pre...
<div><p>Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, ...
The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, th...
Antibiotic resistance is an imminent threat to global health. Patient treatment regimens are often s...
Training and test images of live, membrane-labeled E. coli cells for prediction of SIM super-resolut...
The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, th...
The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, th...
In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies...
The model files and data sets are related to publications of: 1) the research article "Li, C., Suth...
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless a...