Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP
The study developed an artificial intelligence-driven system for quantifying antibiotic-resistant bacteria in food using a color-encoded multiplex hydrogel digital loop-mediated isothermal amplification (LAMP) system. The system uses fluorophores to generate color-specific fluorescent spots, which are then identified and quantified using a deep learning model. This technology has potential for digital quantification in the food industry.
OUR UNDERWRITERS
Unrestricted financial support by:
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Antimicrobial Resistance Fighter Coalition |
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Bangalore Bioinnovation Centre |
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INTERNATIONAL FEDERATION PHARMACEUTICAL MANUFACTURERS & ASSOCIATIONS |
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BD |
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