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Classification of urine components using supervised machine learning based on physical particle data retrieved by digital holographic microscopy

Yussef Hanna,Marlene Kallaß,Álvaro Barroso,Jürgen Schnekenburger,Klaus Brinker,Björn Kemper

Digital Holography and 3-D Imaging 2022（2022）

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Abstract
We explored the capabilities of supervised machine learning to classify urine sediment based on physical parameters retrieved from quantitative digital holographic phase contrast images.
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Key words
urine components,physical particle data,supervised machine learning,classification
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