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Dataset

Deep Antimicrobial Susceptibility Phenotyping (DASP) Training and Evaluation Dataset, and Trained Models.

Documentation:
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-Testing

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Condensed Matter Physics
Research group:
Kavli Institute for Nanoscience Discovery
Oxford college:
Keble College
Role:
Data steward, Researcher, Creator
More by this author/creator
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Condensed Matter Physics
Research group:
Kavli Institute for Nanoscience Discovery
Role:
Researcher, Creator
ORCID:
0000-0002-3644-0636
More by this author/creator
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Researcher, Creator
More by this author/creator
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Principal Investigator (PI), Creator
ORCID:
0000-0002-4508-7969
More by this author/creator
Institution:
University of Oxford
Division:
MSD
Department:
Women's & Reproductive Health
Role:
Principal Investigator (PI), Creator
ORCID:
0000-0002-2887-2068


More from this funder
Funder identifier:
http://dx.doi.org/10.13039/501100000266
Grant:
EP/L016052/1
Programme:
Oxford-Nottingham Biomedical Imaging Centre for Doctoral Training
More from this funder
Funder identifier:
http://dx.doi.org/10.13039/501100004211
Programme:
Oxford Martin School Programme on Antimicrobial Resistance Testing
More from this funder
Funder identifier:
http://dx.doi.org/10.13039/100010269
Grant:
110164/Z/15/Z
More from this funder
Funder identifier:
http://dx.doi.org/10.13039/501100000268
Grant:
BB/N018656/1
BB/S008896/1


Publisher:
University of Oxford
Publication date:
2023
Spatial coverage:
Oxford
DOI:
Temporal coverage:
2020 - 2022
Data collected:
2020-08-20 - 2022-09-20

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