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Predicting abandonment in telehomecare programs using Sentiment Analysis: a system proposal

机译:使用情感分析预测电视社会方案的放弃:系统提案

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In the last decades, an increasing attention was posed towards the management and treatment of chronic diseases. This as led to a consequent need of making patients more active in the treatment of their illness (patients empowerment) and to the ever-increasing introduction of telehealth, telemedicine and telehomecare systems. Even though telemedicine services have been proved to improve many aspects of patients' care, studies have also shown that a relevant percentage of patients abandon telemedicine programs. In this work, a system architecture is proposed in order to monitoring patient's opinion about a telehomecare service. The presented architecture is composed by three main steps: the development of survey instrument defining a systematic survey's a survey tool for administrating questions to patients, an analysis module that will perform both Sentiment analysis and Emotion mining on open text answers, and more general Machine Learning techniques to monitor patient's opinion and make predictions about patients dropout.
机译:在过去的几十年中,对慢性病的管理和治疗提出了越来越大的关注。这导致导致使患者在治疗其疾病(患者赋权)和远程介绍的患者中,以使患者更加活跃,并且越来越多地引入远程医疗和电视传播系统。尽管已经证明了远程医疗服务改善了患者护理的许多方面,但研究也表明,相关百分比的患者放弃远程医疗计划。在这项工作中,提出了一种系统架构,以监测患者对电视管理服务的看法。呈现的架构由三个主要步骤组成:调查仪器的开发定义系统调查的调查工具,用于向患者提供问题,一个分析模块将在开放文本答案上进行情感分析和情感挖掘,以及更多的一般机器学习监测患者意见和预测对患者辍学的技术。

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