Self-improving method of using online communities to predict health-related outcomes
    1.
    发明授权
    Self-improving method of using online communities to predict health-related outcomes 有权
    使用在线社区预测健康相关结果的自我改进方法

    公开(公告)号:US09589104B2

    公开(公告)日:2017-03-07

    申请号:US12251189

    申请日:2008-10-14

    摘要: The invention is directed, in part, to method of using self-reported health data in online communities to predict significant health events in life-changing illnesses to improve the lives of individuals and to improve patient self-management. The invention provides a method for providing real-time personalized medical predictions for an individual patient. The method includes: providing a database containing patient information for a plurality of other patients including one or more attributes for each patient in the database; constructing a model of a disease based on disease progressions for the plurality of patients; receiving a request from the individual patient, the patient associated with one or more attributes; and making a real-time prediction for the individual patient based on the mode and the individual patient's attributes.

    摘要翻译: 本发明部分地涉及在在线社区中使用自我报告的健康数据来预测改变生命的疾病中的重要健康事件以改善个体的生活并改善患者自我管理的方法。 本发明提供了一种用于为个体患者提供实时个性化医疗预测的方法。 该方法包括:提供包含多个其他患者的患者信息的数据库,包括数据库中每个患者的一个或多个属性; 基于多个患者的疾病进展构建疾病模型; 从个体患者接收与一个或多个属性相关联的患者的请求; 并且基于模式和个体患者的属性对个体患者进行实时预测。

    PERSONALIZED MANAGEMENT AND MONITORING OF MEDICAL CONDITIONS
    2.
    发明申请
    PERSONALIZED MANAGEMENT AND MONITORING OF MEDICAL CONDITIONS 审中-公开
    个人化管理和医疗条件监测

    公开(公告)号:US20090144089A1

    公开(公告)日:2009-06-04

    申请号:US12250889

    申请日:2008-10-14

    IPC分类号: G06Q50/00 G06Q90/00

    摘要: The invention provides a system and a method for tracking, assessing, and managing personalized data related to medical conditions, diseases, disease symptoms, treatments, body function metrics, health and well-being, education, and training. In one embodiment, a method for personalized management of a medical condition is provided. The method includes providing a graphical user interface for allowing the patient to input at least one medical condition metric and at least one intervention, receiving at least one medical condition metric for a patient for a time interval, receiving information about at least one intervention for the patient for the time interval, and displaying the at least one medical condition metric and intervention over the time interval.

    摘要翻译: 本发明提供了一种用于跟踪,评估和管理与医疗状况,疾病,疾病症状,治疗,身体功能指标,健康和福祉,教育和训练有关的个性化数据的系统和方法。 在一个实施例中,提供了用于医疗状况的个性化管理的方法。 该方法包括提供用于允许患者输入至少一个医疗状况量度和至少一个干预的图形用户界面,在一段时间间隔内接收患者的至少一个医疗状态度量,接收关于至少一个干预的信息 患者的时间间隔,并且在时间间隔上显示至少一个医疗状况度量和干预。

    SELF-IMPROVING METHOD OF USING ONLINE COMMUNITIES TO PREDICT HEALTH-RELATED OUTCOMES
    3.
    发明申请
    SELF-IMPROVING METHOD OF USING ONLINE COMMUNITIES TO PREDICT HEALTH-RELATED OUTCOMES 审中-公开
    使用在线社区预防健康相关成果的自我改进方法

    公开(公告)号:US20090131758A1

    公开(公告)日:2009-05-21

    申请号:US12251189

    申请日:2008-10-14

    IPC分类号: A61B5/00

    摘要: The invention is directed, in part, to method of using self-reported health data in online communities to predict significant health events in life-changing illnesses to improve the lives of individuals and to improve patient self-management. The invention provides a method for providing real-time personalized medical predictions for an individual patient. The method includes: providing a database containing patient information for a plurality of other patients including one or more attributes for each patient in the database; constructing a model of a disease based on disease progressions for the plurality of patients; receiving a request from the individual patient, the patient associated with one or more attributes; and making a real-time prediction for the individual patient based on the mode and the individual patient's attributes.

    摘要翻译: 本发明部分地涉及在在线社区中使用自我报告的健康数据来预测改变生命的疾病中的重要健康事件以改善个体的生活并改善患者自我管理的方法。 本发明提供了一种用于为个体患者提供实时个性化医疗预测的方法。 该方法包括:提供包含多个其他患者的患者信息的数据库,包括数据库中每个患者的一个或多个属性; 基于多个患者的疾病进展构建疾病模型; 从个体患者接收与一个或多个属性相关联的患者的请求; 并且基于模式和个体患者的属性对个体患者进行实时预测。