New paper: a deep learning model that reads MICs from images of 96 well plates
antimicrobial resistance
computing
tuberculosis

Our paper describing how a convolutional neural network model can determine the minimum inhibitory concentrations (MICs) from a photograph of the 96-well plate after two weeks incubation has been published in the Computational and Structural Biology Journal. You can get the model, which is called TMAS, on GitHub here and there is a longer description here.