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SYSTEMS AND METHODS FOR PREDICTING POST-OPERATIVE RIGHT VENTRICULAR FAILURE USING ECHOCARDIOGRAMS

机译:使用超声心动图预测术后右心室失效的系统和方法

摘要

Systems and methods for incorporating machine learning to predict post operative right ventricular failure using echocardiograms are described. In an embodiment, the system obtains echocardiography video data describing a patient's heart, generates several dense trajectory descriptors based on the echocardiography video data, reduces the dense trajectory descriptors to a bag-of-words representation, generates a first prediction metric of RV failure based on the bag-of-words representation, generates a second prediction metric based on the echocardiography video data using a neural network, and generates an output prediction metric by applying a weighted classifier to the first prediction metric and the second prediction metric.
机译:描述了用于将机器学习的系统和方法预测使用超声心动图预测术后右心室失效。 在一个实施例中,系统获得描述患者心脏的超声心动图视频数据,基于超声心动图视频数据生成多个致密轨迹描述符,将致密的轨迹描述符减少到单词袋式表示,生成基于RV失败的第一预测度量 在单词袋式表示上,使用神经网络基于超声心动图视频数据生成第二预测度量,并通过将加权分类器应用于第一预测度量和第二预测度量来生成输出预测度量。

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