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    • 1. 发明申请
    • PATIENT CONDITION DETECTION AND MORTALITY
    • 患者状况检测和死亡率
    • WO2012085750A1
    • 2012-06-28
    • PCT/IB2011/055610
    • 2011-12-12
    • KONINKLIJKE PHILIPS ELECTRONICS N.V.CHBAT, Nicolas, Wadih
    • CHBAT, Nicolas, Wadih
    • G06F19/30
    • G06F19/345G06F19/00G16H50/20
    • When prediction onset of a medical condition for a patient, multiple sources of knowledge (112) are aggregated and modeled into a format that is usable by multiple algorithms including an inference algorithm (134), a Bayesian network (136), and a state machine (138). The outputs (116) of the multiple algorithms are then combined to more accurately predict condition onset. For instance, several knowledge sources can be input to each of the inference algorithm, the Bayesian network, and the finite state machine, and the outputs of each algorithm are combined, optionally weighted, etc., to make a final determination of the likelihood that the patient has or will imminently have the specified medical condition.
    • 当患者的医疗状况的预测开始时,多个知识源(112)被聚合并被建模为可由多种算法使用的格式,包括推理算法(134),贝叶斯网络(136)和状态机 (138)。 然后将多个算法的输出(116)组合以更准确地预测条件发作。 例如,可以向每个推理算法,贝叶斯网络和有限状态机输入几个知识源,并且将每个算法的输出组合,可选地加权等,以最终确定可能性 患者已经或将会立即具有指定的医疗状况。