基于“自由文本分析”的医疗保健行业患者服务质量反馈平台

Ahthasham Sajid, M. Awais, Mirza Amir Mehmood, S. Batool, Amir Shahzad, A. Zafar
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引用次数: 1

摘要

对社交媒体帖子的数据分析继续提供有关个人面临的健康状况的各种信息。社交网络或社交媒体网站为我们提供了用户在各个领域生成的大量信息,这些生成的信息是非结构化的,未标记的,并且没有以非常系统的方式捕获,因为生成的信息由于其大小而不可能被人类处理。收集病人经验的一种传统方法是进行调查和问卷调查,因为这些方法会问固定的问题,而且管理起来很昂贵。本文开发了一个利用自由文本情感分析的患者反馈平台(PFP),用于计算识别和分类文本中表达的极性。结果显示,在预测病人是否会推荐这项服务方面,准确率达到88%。在此基础上,建议将开发的(PFP)患者反馈平台用于改进电子医疗保健服务。
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Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry
Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patient's experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Results achieved have shown 88 % accuracy in predicting whether or not a patient will recommend the service. Based on which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed.
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