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A Predictive Model for Acute Admission in Aged Population

机译:年龄人口急性入学的预测模型

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Acute hospital admission among the elderly population is very common and have a high impact on the health services and the community, as well as on the individuals. Several studies have focused on the possible risk factors, however, predicting who is at risk for acute hospitalization associated with disease and symptoms is still an open research question. In this study, we investigate the use of machine learning algorithms for predicting acute admission in older people based on admission data from individual citizens 70 years and older who were hospitalized in the acute medical unit of Svendborg Hospital in Denmark.
机译:老年人口中的急性医院入院是非常普遍的,对卫生服务和社区以及个人产生高影响力。几项研究专注于可能的危险因素,然而,预测患有与疾病和症状相关的急性住院风险仍然是一个开放的研究问题。在这项研究中,我们研究了机器学习算法的使用,以便根据丹麦急性医院急性医院住院的个人公民和住院的个人公民的入场数据来预测老年人的急性入学。

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