This project aims to develop and bring to market a point-of-care test (POCT) device driven by artificial intelligence to identify pathogenic yeast species from microscopy images collected from clinical samples (blood and urine). We will evaluate the efficacy of microfluidic devices to aid in the capture of microscopy images of different yeast species and their […]
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