A Review on the Role of Nano-Communication in Future Healthcare Systems: A Big Data Analytics Perspective
TL;DR: A first-time review of the open literature focused on the significance of big data generated within nano-sensors and nano-communication networks intended for the future healthcare and biomedical applications is presented.
Abstract: This paper presents a first-time review of the open literature focused on the significance of big data generated within nano-sensors and nano-communication networks intended for the future healthcare and biomedical applications. It is aimed toward the development of modern smart healthcare systems enabled with P4, i.e., predictive, preventive, personalized, and participatory capabilities to perform diagnostics, monitoring, and treatment. The analytical capabilities that can be produced from the substantial amount of data gathered in such networks will aid in exploiting the practical intelligence and learning capabilities that could be further integrated with conventional medical and health data leading to more efficient decision making. We have also proposed a big data analytics framework for gathering intelligence, form the healthcare big data, required by futuristic smart healthcare to address relevant problems and exploit possible opportunities in the future applications. Finally, the open challenges, the future directions for researchers in the evolving healthcare domain, are presented.
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TL;DR: The Internet of Nano Things and Tactile Internet are driving the innovation in the H-IoT applications and the future course for improving the Quality of Service (QoS) using these new technologies are identified.
Abstract: The impact of the Internet of Things (IoT) on the advancement of the healthcare industry is immense. The ushering of the Medicine 4.0 has resulted in an increased effort to develop platforms, both at the hardware level as well as the underlying software level. This vision has led to the development of Healthcare IoT (H-IoT) systems. The basic enabling technologies include the communication systems between the sensing nodes and the processors; and the processing algorithms for generating an output from the data collected by the sensors. However, at present, these enabling technologies are also supported by several new technologies. The use of Artificial Intelligence (AI) has transformed the H-IoT systems at almost every level. The fog/edge paradigm is bringing the computing power close to the deployed network and hence mitigating many challenges in the process. While the big data allows handling an enormous amount of data. Additionally, the Software Defined Networks (SDNs) bring flexibility to the system while the blockchains are finding the most novel use cases in H-IoT systems. The Internet of Nano Things (IoNT) and Tactile Internet (TI) are driving the innovation in the H-IoT applications. This paper delves into the ways these technologies are transforming the H-IoT systems and also identifies the future course for improving the Quality of Service (QoS) using these new technologies.
446 citations
Cites background from "A Review on the Role of Nano-Commun..."
...proactive healthcare instead of reactive healthcare that can not only detect infections, injuries, or diseases as soon as they happen but, even before they start [237]....
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TL;DR: This paper surveys the application and implementation of differential privacy in four major applications of CPSs named as energy systems, transportation systems, healthcare and medical systems, and industrial Internet of things (IIoT).
Abstract: Modern cyber physical systems (CPSs) has widely being used in our daily lives because of development of information and communication technologies (ICT). With the provision of CPSs, the security and privacy threats associated to these systems are also increasing. Passive attacks are being used by intruders to get access to private information of CPSs. In order to make CPSs data more secure, certain privacy preservation strategies such as encryption, and k-anonymity have been presented in the past. However, with the advances in CPSs architecture, these techniques also need certain modifications. Meanwhile, differential privacy emerged as an efficient technique to protect CPSs data privacy. In this paper, we present a comprehensive survey of differential privacy techniques for CPSs. In particular, we survey the application and implementation of differential privacy in four major applications of CPSs named as energy systems, transportation systems, healthcare and medical systems, and industrial Internet of things (IIoT). Furthermore, we present open issues, challenges, and future research direction for differential privacy techniques for CPSs. This survey can serve as basis for the development of modern differential privacy techniques to address various problems and data privacy scenarios of CPSs.
357 citations
Cites background from "A Review on the Role of Nano-Commun..."
...In majority of cases, the late diagnosis leads to dangerous chronic diseases, certain advanced cancer stages, or even death in some cases [258]....
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TL;DR: It is indicated that medical institutions need to pay attention to data privacy protection and grasp the use of digital medical data to provide decision support for subsequent medical data analysis.
155 citations
TL;DR: The findings indicate that, despite the recency of the subject, research in H4.0 has been conducted in an interdisciplinary way with a diversified set of applications and functionalities.
Abstract: This paper aims at examining the trends, challenges and theoretical gaps in the implementation of Healthcare 4.0 (H4.0) based on a scoping review of the literature. For that, we searched journal ar...
88 citations
TL;DR: An overview of the current THz nanocommunication and nanonetworking research, which discusses the applications envisioned to be supported by nanonetworks operating in the THz band, together with the requirements such applications pose on the underlying nanonetwork.
Abstract: Recent developments in nanotechnology herald nanometer-sized devices expected to bring light to a number of groundbreaking applications. Communication with and among nanodevices will be needed for unlocking the full potential of such applications. As the traditional communication approaches cannot be directly applied in nanocommunication, several alternative paradigms have emerged. Among them, electromagnetic nanocommunication in the terahertz (THz) frequency band is particularly promising, mainly due to the breakthrough of novel materials such as graphene. For this reason, numerous research efforts are nowadays targeting THz band nanocommunication and consequently nanonetworking. As it is expected that these trends will continue in the future, we see it beneficial to summarize the current status in these research domains. In this survey, we therefore aim to provide an overview of the current THz nanocommunication and nanonetworking research. Specifically, we discuss the applications envisioned to be supported by nanonetworks operating in the THz band, together with the requirements such applications pose on the underlying nanonetworks. Subsequently, we provide an overview of the current contributions on the different layers of the protocol stack, as well as the available channel models and experimentation tools. Finally, we identify a number of open research challenges and outline several future research directions.
62 citations
Cites background from "A Review on the Role of Nano-Commun..."
...In addition, [36] briefly discusses electromagnetic communication from a stand-point of future healthcare systems, with the main focus of the work being big data analytics for healthcare data....
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...In order to position our work in the context of the above-outlined contributions (summarized in Table I), it is first relevant to note that these contributions, apart from [36], [37], date from 2016 or before....
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References
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01 Jan 2006TL;DR: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.
Abstract: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.
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TL;DR: The principles of the method and how to impute categorical and quantitative variables, including skewed variables, are described and shown and the practical analysis of multiply imputed data is described, including model building and model checking.
Abstract: Multiple imputation by chained equations is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including skewed variables. We give guidance on how to specify the imputation model and how many imputations are needed. We describe the practical analysis of multiply imputed data, including model building and model checking. We stress the limitations of the method and discuss the possible pitfalls. We illustrate the ideas using a data set in mental health, giving Stata code fragments. Copyright © 2010 John Wiley & Sons, Ltd.
6,349 citations
"A Review on the Role of Nano-Commun..." refers methods in this paper
...[85] discuss in detail a method of multiple imputation using chained equations (MICE) and [80] recommends it as one of very effective approach for handling missing values....
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TL;DR: The need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats is highlighted and the need to devise new tools for predictive analytics for structured big data is reinforced.
2,962 citations
"A Review on the Role of Nano-Commun..." refers background in this paper
...In addition to the three V’s, other dimensions of big data have also been mentioned like Veracity, Variability (complexity) and Value, terms are introduced by IBM, SAS and Oracle respectively [58]....
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TL;DR: The background and state-of-the-art of big data are reviewed, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid, as well as related technologies.
Abstract: In this paper, we review the background and state-of-the-art of big data. We first introduce the general background of big data and review related technologies, such as could computing, Internet of Things, data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition, data storage, and data analysis. For each phase, we introduce the general background, discuss the technical challenges, and review the latest advances. We finally examine the several representative applications of big data, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid. These discussions aim to provide a comprehensive overview and big-picture to readers of this exciting area. This survey is concluded with a discussion of open problems and future directions.
2,303 citations
"A Review on the Role of Nano-Commun..." refers background in this paper
...However, the general consensus to describe big data is based on four major attributes (4Vs) [59], which are discussed as follows: Volume: Consider an implementation scheme for ubiquitous sensing with millions of nano-sensors in and off body networks....
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07 Feb 2014
TL;DR: Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs, and its potential is great; however there remain challenges to overcome.
Abstract: Objective: To describe the promise and potential of big data analytics in healthcare. Methods: The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. Results: The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Conclusions: Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.
2,272 citations
"A Review on the Role of Nano-Commun..." refers background in this paper
...There already exists an ongoing debate on the possible role of big data analytics in healthcare [5], [6], [8], [61], [62], and its practical implications [63]–[66] that is very promising....
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...There are also many examples in the literature where applications [7], potential role [8], possible implementation frameworks [9] and steps involved in analysis are discussed thoroughly for big data from conventional sources....
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