A twin convolutional neural network with hybrid binary optimizer for multimodal breast cancer digital image classification

Abstract There is a wide application of deep learning technique to unimodal medical image analysis with significant classification accuracy performance observed.However, real-world diagnosis of some chronic diseases such as breast cancer often require multimodal data streams with different modalities of visual and textual content.Mammography, magne

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Recent advances in nano-photonic techniques for pharmaceutical drug monitoring with emphasis on Raman spectroscopy

Innovations in Raman spectroscopic techniques provide a potential solution to current problems in pharmaceutical drug monitoring.This review aims to summarize the recent advances in the field.The developments of novel plasmonic nanoparticles continuously push the limits of Raman spectroscopic detection.In surface-enhanced Raman spectroscopy (SERS),

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Cardiovascular magnetic resonance findings in a pediatric population with isolated left ventricular non-compaction

Abstract Background Isolated Left Ventricular Non-compaction (LVNC) is an uncommon disorder characterized by the presence of increased trabeculations and deep intertrabecular recesses.In adults, it has been found that Ejection Fraction (EF) decreases significantly as non-compaction severity increases.In children however, there are a few data descri

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