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首页> 外文期刊>Evidence-based complementary and alternative medicine: eCAM >Study of the Relationship between ICU Patient Recovery and TCM Treatment in Acute Phase: A Retrospective Study Based on Python Data Mining Technology
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Study of the Relationship between ICU Patient Recovery and TCM Treatment in Acute Phase: A Retrospective Study Based on Python Data Mining Technology

机译:急性期ICU患者恢复与中医治疗的关系研究:基于Python数据挖掘技术的回顾性研究

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Background . Data was mined with the help of an artificial intelligence system based on Python, data was collected, and a database was established using a Python crawler, and the relationship between the outcome of neurosurgery ICU patients and treatment using traditional Chinese medicine was ascertained through data management and statistical processing. Method . The source data cases ( n ?=?2237) were selected. By following the experimental design, data ( n ?=?739) were obtained through artificial intelligence processing, including n ?=?480 in the group with traditional Chinese medicine treatment and n ?=?259 in the group without traditional Chinese medicine treatment. An evaluation was carried out using characteristics of patents’ ICU stays and summated rating scales. Results . There were statistical differences in 5 evaluation items ( ), and other comparison items also showed data with results favoring the outcomes in the intervention group using traditional Chinese medicine. Discussion . Traditional Chinese medicine as an alternative medical protocol effectively alleviates the stress and treatment fatigue brought about by modern medicine. Artificial intelligence data mining is a favorable medium to quantify this. Python will play a greater role in future clinical research because of its own characteristics.
机译:背景 。在基于Python的人工智能系统的帮助下开采了数据,收集了数据,并使用蟒蛇履带建立了一个数据库,并通过数据管理确定了神经外科ICU患者的结果与治疗的关系和统计处理。方法 。选择源数据情况(n?=Δ2237)。通过遵循实验设计,通过人工智能处理获得数据(N?=α739),包括N?= 480,中医治疗,N?= 259在没有中医治疗的情况下。利用专利ICU的特征进行了评估,并进行了总结评级尺度。结果 。 5评估项目()中存在统计差异,其他比较项目还显示了使用中医的干预组的结果的数据。讨论 。作为替代医学方案的中医有效减轻了现代医学所带来的压力和治疗疲劳。人工智能数据挖掘是一种有利的媒体,可以量化这一点。由于自己的特点,Python将在未来的临床研究中发挥更大的作用。

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