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Graphic Visualization of the Co-Occurrence Analysis Network of Lung Cancer In-Patient Nursing Record

机译:肺癌患者护理记录共现分析网络的图形可视化

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摘要

Although the nursing record provides a complete account of a patient's information, it is not fully utilized. The relevant information including laboratory results, remarks made by doctors and nurses is not taken into consideration. Knowledge concerning the condition and treatment of patients has been determined in a twofold manner: a text mining technique has identified relations between feature vocabularies seen in past lung cancer in-patient records accumulated on University of Miyazaki Hospital electronic medical record, and an extraction has been attempted to solve the above-mentioned problem in the present study. The result was an analysis of a qualitative lung cancer in- patients' nursing record that used the text mining technique, and the initial goal was achieved: a visual record of this information. In addition, this enabled the discovery of vocabularies relating to the proper methods of treatment, resulting in a concise summary of the vocabularies extracted from the content of the lung cancer in-patients' nursing record. Important vocabularies characterizing each nursing record were also revealed.
机译:尽管护理记录提供了患者信息的完整说明,但并未充分利用。包括实验室结果,医生和护士的评论在内的相关信息均未考虑在内。关于患者病情和治疗的知识已经以两种方式确定:一种文字挖掘技术已经确定了在宫崎大学医院电子病历中积累的以往肺癌住院记录中所见特征词之间的关系,并且已经提取了试图解决本研究中的上述问题。结果是使用文本挖掘技术对定性肺癌患者的护理记录进行了分析,并且达到了最初的目标:对这些信息进行可视化记录。此外,这使发现与正确治疗方法有关的词汇成为可能,从而使从肺癌住院患者护理记录中提取的词汇简明扼要。还揭示了表征每个护理记录的重要词汇。

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