The significant increase in the number of individuals with chronic ailments (including the elderly and disabled) has dictated an urgent need for an innovative model for healthcare systems. The evolved model will be more personalized and less reliant on traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes, and long-term healthcare centers. The smart healthcare system is a topic of recently growing interest and has become increasingly required due to major developments in modern technologies, especially in artificial intelligence (AI) and machine learning (ML). This paper is aimed to discuss the current state-of-the-art smart healthcare systems highlighting major areas like wearable and smartphone devices for health monitoring, machine learning for disease diagnosis, and the assistive frameworks, including social robots developed for the ambient assisted living environment. Additionally, the paper demonstrates software integration architectures that are very significant to create smart healthcare systems, integrating seamlessly the benefit of data analytics and other tools of AI. The explained developed systems focus on several facets: the contribution of each developed framework, the detailed working procedure, the performance as outcomes, and the comparative merits and limitations. The current research challenges with potential future directions are addressed to highlight the drawbacks of existing systems and the possible methods to introduce novel frameworks, respectively. This review aims at providing comprehensive insights into the recent developments of smart healthcare systems to equip experts to contribute to the field.
翻译:由于慢性病患者(包括老年人和残疾人)人数的大量增加,迫切需要为保健系统建立一个创新模式,进化后的模式将更加个性化,减少对医院、疗养院和长期保健中心等传统制砖和成模保健机构的依赖。智能保健系统是最近人们日益感兴趣的一个专题,由于现代技术的重大发展,特别是人工智能(AI)和机器学习(ML)的重大发展,因此越来越需要智能保健系统。本文件的目的是讨论目前最先进的智能保健系统,强调主要领域,例如用于健康监测的可磨机和智能手机设备、疾病诊断的机器学习以及辅助性框架,包括为环境辅助生活环境开发的社会机器人。此外,文件展示了对创建智能保健系统非常重要的软件整合结构,将数据分析器和其他工具的惠益紧密地结合起来。解释发达的系统侧重于几个方面:每个发达框架的贡献、详细的工作程序、结果的绩效以及比较优点和局限性。目前与未来方向有关的研究挑战,包括环境辅助性居住环境环境环境环境环境环境环境环境环境环境的开发的社会机器人。此外,文件还展示了软件整合结构,这些结构对于创建智能系统非常重要,将顺利地整合数据分析和其他工具的惠益。解释系统。解释各种系统。解释系统的重点系统的重点侧重于系统将分别纳入现有系统。