Abstract
Arterial duplex ultrasound is a noninvasive and readily available imaging study that plays an important role in the diagnosis and surveillance of peripheral artery disease. A component of the duplex ultrasound interpretation includes classification of the Doppler waveforms into triphasic, biphasic, monophasic, and occluded, with the latter two considered abnormal. We sought to use machine learning techniques to automate the classification of the Doppler waveforms.
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