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Patient situation predicting device, prediction model generation device, patient situation prediction program and patient situation prediction method

机译:患者情况预测装置,预测模型生成装置,患者情况预测计划和患者情况预测方法

摘要

The present invention is provided with: a residual-drowsiness prediction model generating unit 13 for generating a residual-drowsiness prediction model for predicting the presence/absence of residual drowsiness on the basis of CPAP device data, using, as learning data, CPAP device data obtained from a breathing device used in CPAP treatment, relating to a plurality of patients affected by sleep apnea syndrome, and activity meter data measured over time by activity meters used while worn on the bodies of the plurality of patients; and a residual-drowsiness prediction unit 14 for predicting the presence/absence of residual drowsiness in a patient as a prediction subject, by applying prediction data to the residual-drowsiness prediction model, using the CPAP device data relating to the prediction subject patient as the prediction data; and the present invention is configured so that when there are CPAP device data relating to the breathing device used by the prediction subject patient for CPAP treatment, residual drowsiness in the patient receiving CPAP treatment can be objectively ascertained by applying the CPAP device data as prediction data to the residual-drowsiness prediction model.
机译:本发明提供了:残余困难的预测模型生成单元13,用于基于CPAP设备数据,使用作为学习数据,CPAP设备数据的基于CPAP设备数据来生成残差嗜睡预测模型,用于预测残留困难预测模型。从CPAP治疗中使用的呼吸装置获得,与受睡眠呼吸暂停综合征影响的多个患者有关,以及在多个患者的身体上穿过时使用的活动仪表测量的活动仪表数据;和残留嗜睡预测单元14通过将预测数据应用于剩余困难的预测模型,使用与预测对象患者有关的CPAP设备数据作为预测对象预测患者在患者中作为预测对象的残留嗜睡的存在/不存在。预测数据;并且本发明被配置为使得当存在与由预测对象患者使用的呼吸装置有关的CPAP处理有关的CPAP设备数据时,可以通过将CPAP设备数据应用为预测数据来客观地确定接收CPAP处理的患者中的残余困难到残余嗜睡预测模型。

著录项

  • 公开/公告号JP6884453B2

    专利类型

  • 公开/公告日2021-06-09

    原文格式PDF

  • 申请/专利权人 サスメド株式会社;

    申请/专利号JP20200556531

  • 发明设计人 上野 太郎;市川 太祐;本橋 智光;

    申请日2018-11-15

  • 分类号A61M16;G16H10;G16H20;G16H40/40;A61B5/16;

  • 国家 JP

  • 入库时间 2022-08-24 19:06:33

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