Abstract
The advances in information technology have facilitated great progress in healthcare technologies in various domains. However, these new technologies have also made healthcare data not only much larger in size but also substantially more difficult to handle and process. Moreover, because the data are created from a variety of devices within a short time span, these data are stored in different formats and created quickly, which can to a large extent be regarded as a big data problem. This paper discusses how to develop intelligent patientcentric healthcare applications and services from the perspectives of mobile computing and big data analytics technologies. This healthcare system consists of a data collection layer with a unified standard, a data management layer for distributed storage and parallel computing, and a data-oriented service layer. Furthermore, various healthcare applications are discussed to show that mobile computing and big data technologies enhance the performance of the system toward improving a humans well-being.
Highlights
In the past two decades, advanced information technologies, such as mobile communication systems [1], big data [2], Internet of Things (IoT) [3], and wearable computing [4], have been widely used in the sector of healthcare [5]
To support the efficient management and analysis of medical data, this layer consists of a Distributed File Storage (DFS) and Distributed Parallel Computing (DPC)
Assisted by machine learning, data mining, artificial intelligence, and other advanced techniques, healthcare systems could play an important role as a guide of healthy lifestyles, as a tool to support decision making, and as a source of innovation in the evolving healthcare ecosystem
Summary
In the past two decades, advanced information technologies, such as mobile communication systems [1], big data [2], Internet of Things (IoT) [3], and wearable computing [4], have been widely used in the sector of healthcare [5]. Various novel healthcare systems assisted by big data and mobile computing are developed for provide intelligent and professional services [6]. A huge number of researches focus on data analysis or data mining for healthcare data [10, 20] on technical details in deploying and implementing mobile computing [21, 22], but one of the greatest challenges is how to develop a comprehensive healthcare system for effectively manage multisource heterogeneous healthcare data with particular technical features. This paper presents a detailed design of intelligent healthcare systems assisted by data analytics and mobile computing, and it make the following contributions: (1) It proposes a unified data collection layer for integrating the healthcare data from public sources and personal devices. This paper presents a detailed design of intelligent healthcare systems assisted by data analytics and mobile computing, and it make the following contributions: (1) It proposes a unified data collection layer for integrating the healthcare data from public sources and personal devices. (2) It establishes a cloud-enabled and data-driven platform for multisource heterogeneous healthcare data storage and analysis. (3) It designs a healthcare application service layer to provide unified application programming interface (API) for developers and unified interface for users
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