Microscopy data, analysis code, and segmentation models for Phenotypic drug susceptibility testing for Mycobacterium tuberculosis variant bovis BCG in 12-hour

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Provided by Uppsala universitet

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Dataset information

Country of origin
Updated
2025.12.15 00:00
Created
2025.12.15
Available languages
English
Keywords
Infectious agents, Bacteriology
Quality scoring

Dataset description

The study aimed to improve the speed of drug susceptibility testing for tuberculosis (TB), particularly drug-resistant strains. Current phenotypic drug susceptibility testing (pDST) methods take at least two weeks. This study used microfluidic chips, microscopy, and deep neural network algorithms to monitor the growth of Mycobacterium bovis Bacillus Calmette–Guérin (BCG) and Mycobacterium smegmatis in the presence of antibiotics. The findings suggest that pDST for TB could potentially be completed in less than 12 hours for slow-growing mycobacteria, offering a significant improvement in diagnosing drug-resistant TB. The entry contains raw microscopy data, analysis code and output, and code to generate figures.
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190K+
indexed dataset pages
32
countries and EU institutions
2019
API-first since
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for evaluation and prototypes
SLA
history and push on production APIs
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