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    METHODS AND SYSTEMS FOR CALCULATING AND USING STATISTICAL MODELS TO PREDICT MEDICAL EVENTS
    1.
    发明申请
    METHODS AND SYSTEMS FOR CALCULATING AND USING STATISTICAL MODELS TO PREDICT MEDICAL EVENTS 审中-公开
    计算和使用统计模型预测医疗活动的方法和系统

    公开(公告)号：WO2014036173A1

    公开(公告)日：2014-03-06

    申请号：PCT/US2013/057137

    申请日：2013-08-28

    Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

    Inventor： SARRAFZADEH, Majid ,  SUH, Myung-Kyung ,  LAN, Mars ,  GHASEMZADEH, Hassan

    IPC: G06F19/00

    CPC classification number: A61B5/7282 ,  A61B5/02055 ,  A61B5/0402 ,  A61B5/0476 ,  A61B5/112 ,  A61B5/4094 ,  A61B5/4818 ,  A61B5/725 ,  A61B5/726 ,  A61B5/7264 ,  A61B5/746 ,  F04C2270/041 ,  G06F19/00 ,  G06N99/005 ,  G16H50/20

    Abstract: Systems and methods for generalized precursor pattern discovery that work with a wide range of biomedical signals and applications to detect a wide range of medical events are disclosed. In some embodiments, the methods and systems do not require domain- specific knowledge or significant reconfiguration based on the medical event being analyzed, hence it is also possible to discover patterns previously unknown to experts. In some embodiments, to build precursor pattern detection models, the system obtains annotated monitoring data. Positive and negative segments are extracted from the annotated monitoring data, and are preprocessed. Features are extracted from the preprocessed segments, and selected features are chosen from the extracted features. The selected features are classified to create the precursor pattern detection model The precursor pattern detection model may then be used in real time to detect occurrences of the medical event of interest.

    Abstract translation: 公开了用于广泛的生物医学信号和应用以检测​​广泛的医疗事件的广泛前体模式发现的系统和方法。 在一些实施例中，方法和系统不需要基于正在分析的医疗事件的特定于领域的知识或重要的重新配置，因此也可以发现先前为专家所未知的模式。 在一些实施例中，为了构建前体模式检测模型，系统获得注释的监视数据。 从注释的监控数据中提取正段和负段，并进行预处理。 从预处理的段中提取特征，并且从所提取的特征中选择所选择的特征。 所选择的特征被分类以创建前体模式检测模型。然后可以实时地使用前体模式检测模型来检测感兴趣的医疗事件的发生。

    SYSTEMS AND METHODS FOR MISSING DATA IMPUTATION
    2.
    发明申请
    SYSTEMS AND METHODS FOR MISSING DATA IMPUTATION 审中-公开
    用于丢失数据传输的系统和方法

    公开(公告)号：WO2013033028A1

    公开(公告)日：2013-03-07

    申请号：PCT/US2012/052544

    申请日：2012-08-27

    Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA ,  SARRAFZADEH, Majid ,  SUH, Myung-Kyung

    Inventor： SARRAFZADEH, Majid ,  SUH, Myung-Kyung

    IPC: A61B5/02 ,  H04B7/24

    CPC classification number: G06F19/322 ,  A61B5/7264 ,  A61B5/7267 ,  G06F19/00 ,  G06F19/3418 ,  G06N7/005 ,  G16H10/60 ,  G16H50/20

    Abstract: 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.

    Abstract translation: 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。

    CONTEXT-AWARE PREDICTION IN MEDICAL SYSTEMS
    8.
    发明申请
    CONTEXT-AWARE PREDICTION IN MEDICAL SYSTEMS 审中-公开
    医学系统中的背景知识预测

    公开(公告)号：WO2014186387A1

    公开(公告)日：2014-11-20

    申请号：PCT/US2014/037887

    申请日：2014-05-13

    Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA ,  GHASEMZADEH, Hassan ,  SUH, Myung-Kyung ,  LAN, Mars ,  SARRAFZADEH, Majid ,  ALSHURAFA, Nabil

    Inventor： GHASEMZADEH, Hassan ,  SUH, Myung-Kyung ,  LAN, Mars ,  SARRAFZADEH, Majid ,  ALSHURAFA, Nabil

    IPC: G06F19/00

    CPC classification number: G16H50/50 ,  G06F19/00

    Abstract: A method includes receiving contextual data related to at least one of environmental, physiological, behavioral, and historical context, and receiving outcome data related to at least one outcome. The method further includes creating a feature set from the contextual data, selecting a subset of features from the feature set, assigning a score to each feature in the subset of features according to the probability that the feature is a predictor of the at least one outcome, and generating a characteristic curve for the at least one outcome from the subset of features, the characteristic curve being based on the scoring. The method further includes calculating the area under the characteristic curve, and using, the area under the characteristic curve, identifying whether the subset of features is a suitable predictor for the at least one outcome.

    Abstract translation: 一种方法包括接收与环境，生理，行为和历史背景中的至少一个相关的上下文数据，以及接收与至少一个结果相关的结果数据。 该方法还包括从上下文数据创建特征集合，从特征集中选择特征的子集，根据特征是至少一个结果的预测因子的概率向特征子集中的每个特征分配得分 并且从所述特征子集生成所述至少一个结果的特征曲线，所述特征曲线基于所述评分。 该方法还包括计算特征曲线下的面积，以及使用特征曲线下的区域来确定特征子集是否是至少一个结果的合适的预测器。

    NON-INVASIVE NUTRITION MONITOR
    9.
    发明申请
    NON-INVASIVE NUTRITION MONITOR 审中-公开
    非营养营养监护仪

    公开(公告)号：WO2014159749A1

    公开(公告)日：2014-10-02

    申请号：PCT/US2014/024976

    申请日：2014-03-12

    Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA ,  WEARSENS INC.

    Inventor： SARRAFZADEH, Majid ,  FALAHI, Misagh ,  ALSHURAFA, Nabil ,  NYAMATHI, Suneil ,  KALANTARIAN, Haik ,  TRAIDMAN, Adam Ryan

    IPC: A61B5/00 ,  G06Q50/22

    CPC classification number: G06F19/3406 ,  A61B5/0002 ,  A61B5/11 ,  A61B5/4205 ,  A61B5/48 ,  A61B5/6822 ,  A61B7/008 ,  G06F19/00 ,  G06Q10/063114 ,  G06Q50/22 ,  G16H40/63

    Abstract: An apparatus includes a sensor configured to detect a variable characteristic, the variation of the characteristic including variation indicative of an individual swallowing when the sensor is positioned in a neck area of the individual. The apparatus includes a wireless data communication interface configured to receive information related to the characteristic and transmit the information externally. The sensor may be, for example, an acoustic sensor, a piezoelectric sensor, a capacitive sensor, or a pressure sensor. The apparatus may include a sensor interface to sample a signal from the sensor and provide data related to the signal for transmission externally. A system may use the information related to the characteristic to identify eating habits and type of food eaten. Feedback may be provided to the individual to help the individual change their dietary intake and habits.

    Abstract translation: 一种装置，包括被配置为检测可变特性的传感器，当所述传感器位于所述个体的颈部区域中时，所述特性的变化包括指示单个吞咽的变化。 该装置包括：无线数据通信接口，被配置为接收与该特性有关的信息，并在外部发送信息。 传感器可以是例如声学传感器，压电传感器，电容式传感器或压力传感器。 该装置可以包括传感器接口，用于对来自传感器的信号进行采样，并提供与用于在外部传输的信号有关的数据。 系统可以使用与特征相关的信息来识别食用习惯和食用食物的类型。 可能会向个人提供反馈意见，以帮助个人改变饮食习惯和饮食习惯。

    SYSTEMS AND METHODS FOR AUTOMATIC SEGMENT SELECTION FOR MULTI-DIMENSIONAL BIOMEDICAL SIGNALS
    10.
    发明申请
    SYSTEMS AND METHODS FOR AUTOMATIC SEGMENT SELECTION FOR MULTI-DIMENSIONAL BIOMEDICAL SIGNALS 审中-公开
    多维生物信号自动选择系统与方法

    公开(公告)号：WO2013112935A1

    公开(公告)日：2013-08-01

    申请号：PCT/US2013/023295

    申请日：2013-01-25

    Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

    Inventor： SARRAFZADEH, Majid ,  LAN, Mars

    IPC: G06Q50/24 ,  G06F19/00 ,  A61B5/0476

    CPC classification number: G06N5/047 ,  A61B5/0476 ,  A61B5/7264 ,  G06F19/00 ,  G06K9/6228 ,  G06N99/005 ,  G16H50/20

    Abstract: Systems and methods for automatically analyzing and selecting prominent channels from multi-dimensional biomedical signals in order to detect particular diseases or ailments are provided. Such systems and methods may be applied in different ways to obtain numerous benefits, such as lowering of power and processing requirements, reducing an amount of data acquired, simplifying hardware deployment, detecting non- trivial patterns, obtaining, clinical episode prognosis, improving patient care, and/or the like.

    Abstract translation: 提供了用于自动分析和选择来自多维生物医学信号的突出信道以检测特定疾病或疾病的系统和方法。 这样的系统和方法可以以不同的方式应用以获得许多益处，例如降低功率和处理要求，减少获取的数据量，简化硬件部署，检测非平凡模式，获得临床事件预后，改善患者护理 ，和/或类似物。

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