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Cardiovascular disease and all-cause mortality risk prediction from abdominal CT using deep learning

机译:心血管疾病和全因死亡率风险预测从腹部CT使用深学习

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摘要

2021 SEP 17 (NewsRx) - By a News Reporter-Staff News Editor at Disease Prevention Daily - According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from medrxiv.org: "Cardiovascular disease is the number one cause of mortality worldwide. Risk prediction can help incentivize lifestyle changes and inform targeted preventative treatment. "In this work we explore utilizing a convolutional neural network (CNN) to predict cardiovascular disease risk from abdominal CT scans taken for routine CT colonography in otherwise healthy patients aged 50-65. "We find that adding a variational autoencoder (VAE) to the CNN classifier improves its accuracy for five year survival prediction (AUC 0.787 vs. 0.768).
机译:2021年9月17日(NewsRx)——由一个新闻记者新闻编辑在日常——疾病预防根据新闻报道基于预印本抽象,我们记者获得以下引用来自medrxiv.org:“心血管疾病是死亡的第一原因在全球范围内。生活方式的改变和通知的目标预防性治疗。利用卷积神经网络(CNN)预测心血管疾病风险腹部CT扫描了常规CT结肠镜在病人的健康50 - 65。autoencoder (VAE) CNN分类器得到改善5年生存预测的准确性(AUC 0.787比0.768)。

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