UbMed:一个无处不在的监测药物依从性的系统

V. Silva, M. Rodrigues, R. Barreto, V. Lucena
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引用次数: 9

摘要

慢性患者在治疗中最大的问题之一是药物依从性。研究表明,逾期服药会影响患者的治疗,降低药物的效果。为了尽量减少这个问题,我们开发了一个无处不在的智能系统,能够监测药物的服用情况,并确定患者是否符合医生的要求。设计了一个基于规则和树的决策系统架构,用于评估从患者家中的智能药柜、传感器和电子设备收集的数据。该系统对服用的药物进行分类,并在社交网络、短信和电视、智能手机、平板电脑等消费电子设备上发布信息,无需人工干预。它的目标是帮助按时服药,并帮助决定在错过正确时间的情况下该怎么做。对J48、Rep和Random tree算法进行了测试,用于对服药模式进行分类,并选择合适的服务。所得结果很有希望,达到了可接受的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UbMed: A ubiquitous system for monitoring medication adherence
One of the biggest problems with chronical patients in treatment is medication adherence. Studies indicate that taking drugs out of time influence the patient's treatment decreasing the drugs effect. To minimize this problem, we developed a ubiquitous and intelligent system able to monitor the taking of medicines and to identify whether the patient is meeting the requirements prescribed by the doctor. An architecture provided with a decision system based on rules and trees to evaluate data collected from an intelligent medicine cabinet, sensors and electronic devices available in the patient's home was designed. The system classified the drugs taken pattern and released messages on social networks, SMS, and consumer electronic devices such as TV, smartphone and tablets, without human interference. Its goal is to help keeping the medication on time and helping to decide what to do in case of missing the right time. The algorithms J48, Rep and Random tree, were tested to classify the taking medicine patterns and to chose the right services available. The obtained results are very promising and reached an acceptable accuracy rate.
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