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Classification of Lung Pathologies in Neonates using Dual Tree Complex Wavelet Transform
Likewise, the proposed method achieved a maximum per-subject classification accuracy of 81. 53% with 43 DTCWT features and 3 clinical features using the balanced dataset and 64. 97% with 13 DTCWT features and 3 clinical features using the unbalanced dataset.
An interpretable object detection based model for the diagnosis of neonatal lung diseases using Ultrasound images
Over the last few decades, Lung Ultrasound (LUS) has been increasingly used to diagnose and monitor different lung diseases in neonates.
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