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A reinforcement learning and deep learning based intelligent system for the support of impaired patients in home treatment
Expert Systems with Applications ( IF 8.5 ) Pub Date : 2020-11-21 , DOI: 10.1016/j.eswa.2020.114285
Muddasar Naeem , Giovanni Paragliola , Antonio Coronato

A clinical treatment process typically carries out in two stages; i.e., hospital stay and treatment at home after hospitalization. The correct completion of the treatment process is essential, but it becomes challenging for elders and patients with any physical or cognitive disability since they need assistance in the execution of the treatment itself.

This work presents an intelligent system able to provide automatic assistance to those patients that have to follow a planned treatment at home. The system can support the patient with both customized reminders whenever it is the time to take medication and alerts to avoid possible medication errors when the patient is going to assume an incorrect drug by mistake. The core of the proposed solution consists of a multi-agent system that relies on algorithms of both Reinforcement Learning and Deep Learning. Experimental results show that the system improves the quality of home assistance services reducing medication errors.



中文翻译:

基于强化学习和深度学习的智能系统,用于为残障患者提供家庭治疗支持

临床治疗过程通常分两个阶段进行:即住院后住院和在家中接受治疗。正确完成治疗过程是必不可少的,但对于具有身体或认知障碍的老年人和患者而言,这变得具有挑战性,因为他们在执行治疗本身时需要帮助。

这项工作提出了一个智能系统,该系统能够为必须在家中进行计划治疗的患者提供自动协助。该系统可以在每次服药时为患者提供定制的提醒,并为患者提供警告,以防止患者误服不正确的药物时可能出现的服药错误。提出的解决方案的核心由一个多主体系统组成,该系统依赖于强化学习和深度学习的算法。实验结果表明,该系统提高了家庭协助服务的质量,减少了用药错误。

更新日期:2020-11-22
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