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AUTOMATED EXTRACTION OF STRUCTURED LABELS FROM MEDICAL TEXT USING DEEP CONVOLUTIONAL NETWORKS AND USE THEREOF TO TRAIN A COMPUTER VISION MODEL
AUTOMATED EXTRACTION OF STRUCTURED LABELS FROM MEDICAL TEXT USING DEEP CONVOLUTIONAL NETWORKS AND USE THEREOF TO TRAIN A COMPUTER VISION MODEL
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机译:使用深度卷积网络从医学文本中自动提取结构化标签,并使用其来训练计算机视觉模型
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摘要
A method is provided for processing medical text and associated medical images. A natural language processor configured as a deep conventional neural network is trained on a first corpus of curated free-text, medical reports each of which having one or more structured labels assigned by an medical expert. The network is trained to learn to read additional free-text medical reports and produce predicted structured labels. The natural language processor is applied to a second corpus of free-text medical reports that are associated with medical images. The natural language processor generates structured labels for the associated medical images. A computer vision model is trained using the medical images and the structured labels generated. The computer vision model can thereafter assign a structured label to a further input medical image. In one example, the medical images are chest X-rays.
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