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      [1]沈鑫陳航黃波楊江存.輸血輔助決策系統構建與應用效果分析[J].中國衛生質量管理,2021,28(08):073-76.[doi:10.13912/j.cnki.chqm.2021.28.8.19 ]
       SHEN Xin,CHEN Hang,HUANG Bo.Construction and Effect Analysis of Blood Transfusion Decision-Making Supporting System[J].Chinese Health Quality Management,2021,28(08):073-76.[doi:10.13912/j.cnki.chqm.2021.28.8.19 ]
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      輸血輔助決策系統構建與應用效果分析
      分享到:

      《中國衛生質量管理》[ISSN:1006-7515/CN:CN 61-1283/R]

      卷:
      第28卷
      期數:
      2021年08期
      頁碼:
      073-76
      欄目:
      血液質量
      出版日期:
      2021-08-28

      文章信息/Info

      Title:
      Construction and Effect Analysis of Blood Transfusion Decision-Making Supporting System
      作者:
      沈鑫陳航黃波楊江存
      陜西省人民醫院
      Author(s):
      SHEN XinCHEN HangHUANG Bo
      Shaanxi Provincial People's Hospital
      關鍵詞:
      輸血輔助決策系統智慧醫療臨床用血精準用血紅細胞輸注
      Keywords:
      Blood Transfusion Decision-Making Supporting System Wisdom Medical Care Clinical Use of Blood Accurate Use of Blood Red Blood Cell Infusion
      分類號:
      R197.3;R331.1
      DOI:
      10.13912/j.cnki.chqm.2021.28.8.19
      文獻標志碼:
      B
      摘要:
      采集醫院HIS、LIS、輸血管理平臺、手術麻醉管理等系統中申請用血、發血、用血相關數據,采用自然語言處理、數據挖掘清洗方式生成用血信息數據庫,基于循環神經網絡及貝葉斯算法等機器學習構建用血智能評估模型,通過臨床紅細胞輸注前后效果評估、歷史用血數據對模型驗證修訂反饋,不斷完善。初步建立了精準、有效的紅細胞輸注輔助決策系統,該系統可為臨床醫師提供紅細胞輸注決策建議,指導臨床合理用血,實現精準用血管理。
      Abstract:
      Data related to blood application, blood delivery and blood consumption were collected from the electronic medical record of hospital information system (HIS), laboratory information system (LIS), blood transfusion management platform and surgical anesthesia management system. The blood information database was generated by natural language processing, data mining and cleaning methods. An intelligent evaluation model of blood consumption was built based on machine learning such as circulating neural network and Bayesian algorithm. The model was continuously improved through the effect evaluation before and after clinical red blood cell infusion and the verification and revision feedback of historical blood data. An accurate and effective decision-making system for red blood cell infusion had been established. The system can provide clinicians with red blood cell transfusion decision suggestions, guide clinical rational blood use, and achieve accurate blood use management.

      參考文獻/References:

      [1]唐吉偉德.建立無償獻血志愿隊應對血荒具有破題之效[EB/OL].(2019-03-15)[2020-02-29].http://view.k618.cn/rmpl/201903/t20190315_17267031.htm. [2]Jo C,Ko S,Shin WC,et al.Transfusion after total knee arthroplasty can be predicted using the machinelearning algorithm[J].Knee Surg Sports Traumatol Arthrosc,2019,7(28):1-8. [3]李 杰,段光友,曾 義,等.人工神經網絡、極端梯度提升和Logistic回歸用于預測再次剖宮產術中輸血的比較分析[J].第三軍醫大學學報,2019,41(24):2430-2437. [4]沈 鑫,常建華,石斌婭,等.基于閉環輸血信息管理平臺的臨床用血管理[J].中國衛生質量管理,2018,25(2):108-110.

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      更新日期/Last Update: 2021-08-28
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