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Found 3 papers, 1 papers with code
Longitudinal detection of radiological abnormalities with time-modulated LSTM
Convolutional neural networks (CNNs) have been successfully employed in recent years for the detection of radiological abnormalities in medical images such as plain x-rays.
Learning to detect chest radiographs containing lung nodules using visual attention networks
We propose two network architectures for the classification of images likely to contain pulmonary nodules using both weak labels and manually-delineated bounding boxes, when these are available.
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks
Motivated by the need to automate medical information extraction from free-text radiological reports, we present a bi-directional long short-term memory (BiLSTM) neural network architecture for modelling radiological language.
Medical Named Entity Recognition
named-entity-recognition
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