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Photoacoustic signatures from different organs like heart, kidney, liver, lungs, and spleen were recorded and subjected to machine-learning-based analysis for discrimination. The outcomes clearly suggest potentiality of machine-learning-enabled photoacoustic spectroscopy in organs classification.
© 2022 The Author(s)
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