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1. 发明申请

US20140207493A1 SYSTEMS AND METHODS FOR MISSING DATA IMPUTATION 审中-公开
标题翻译：用于丢失数据传输的系统和方法
公开(公告)号：US20140207493A1
公开(公告)日：2014-07-24
申请号：US14241431
申请日：2012-08-27
申请人： Majid Sarrafzadeh , Myung-kyung Suh
发明人： Majid Sarrafzadeh , Myung-kyung Suh
IPC分类号： G06F19/00
CPC分类号： G16H10/60 , A61B5/7264 , A61B5/7267 , G06F19/3418 , G06N7/005 , G16H50/20
摘要： Congestive heart failure (CHF) is a leading cause of death in the United States. WANDA is a wireless health project that leverages sensor technology and wireless communication to monitor the health status of patients with CHF. The first pilot study of WANDA showed the system's effectiveness for patients with CHF. However, WANDA experienced a considerable amount of missing data due to system misuse, nonuse, and failure. Missing data is highly undesirable as automated alarms may fail to notify healthcare professionals of potentially dangerous patient conditions. Embodiments of the present disclosure may utilize machine learning techniques including projection adjustment by contribution estimation regression (PACE), Bayesian methods, and voting feature interval (VFI) algorithms to predict both non-binomial and binomial data. The experimental results show that the aforementioned algorithms are superior to other methods with high accuracy and recall.
摘要翻译：充血性心力衰竭（CHF）是美国的主要死亡原因。 WANDA是一个利用传感器技术和无线通信监测CHF患者健康状况的无线健康项目。 WANDA的首例试验研究显示，该系统对CHF患者的疗效。然而，由于系统误用，不用和故障，WANDA遭遇了大量的丢失数据。缺少数据是非常不希望的，因为自动化警报可能无法通知医疗保健专业人员潜在的危险患者状况。本公开的实施例可以利用机器学习技术，包括通过贡献估计回归（PACE）的投影调整，贝叶斯方法和投票特征区间（VFI）算法来预测非二项和二项数据。实验结果表明，上述算法优于其他具有高精度和召回率的方法。

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