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首页> 外文期刊>Frontiers in Public Health >Fatty Liver Disease Prediction Model Based on Big Data of Electronic Physical Examination Records
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Fatty Liver Disease Prediction Model Based on Big Data of Electronic Physical Examination Records

机译:基于电子体检记录大数据的脂肪肝病预测模型

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摘要

Fatty liver disease (FLD) is a common liver disease, which poses a great threat to people's health, but there is still no optimal method that can be used on a large-scale screening. This research is based on machine learning algorithms, using electronic physical examination records in the health database as data support, to a predictive model for FLD. The model has shown good predictive ability on the test set, with its AUC reaching 0.89. Since there are a large number of electronic physical examination records in most of health database, this model might be used as a non-invasive diagnostic tool for FLD for large-scale screening.
机译:脂肪肝病(FLD)是一种常见的肝病,对人们的健康构成了很大的威胁,但仍然没有最佳方法可以在大规模的筛选上使用。 本研究基于机器学习算法,使用健康数据库中的电子物理检查记录作为数据支持,对FLD的预测模型。 该模型在测试集上表现出良好的预测能力,其AUC达到0.89。 由于大多数健康数据库中存在大量电子体检记录,因此该模型可用作FLD的非侵入性诊断工具,用于大规模筛选。

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