On the Application of the Internet of Things in the Field of Medical and Health Care

Hu, Fengxia; Xie, Dan; Shen, Shaowu

doi:10.1109/greencom-ithings-cpscom.2013.384

Cited by 112 publications

(60 citation statements)

References 5 publications

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“…Nevertheless, the exploration of Medical Big Data is linked to a fully-personalized patient care [14,35]. With the emergence of Medical Internet of Things (MIoT), real-time remote monitoring becomes feasible [36][37][38]. By collecting and combining MIoT information with hybrid imaging data, the accuracy of predictive analytics can be increased significantly [38] and can result in automated, Clinical Decision Support systems (CDSS) [39] (Figure 4).…”

Section: Machine Learning For Medical Big Data Analysismentioning

confidence: 99%

“…With the emergence of Medical Internet of Things (MIoT), real-time remote monitoring becomes feasible [36][37][38]. By collecting and combining MIoT information with hybrid imaging data, the accuracy of predictive analytics can be increased significantly [38] and can result in automated, Clinical Decision Support systems (CDSS) [39] (Figure 4). This leads to healthcare approaches that help improve patient comfort and reduce healthcare costs as part of a fully patient-centric, personalized medicine [40] (Figure 5).…”

Section: Machine Learning For Medical Big Data Analysismentioning

confidence: 99%

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Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

et al. 2018

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Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual-or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic), also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid imaging in view of personalized medicine, whereby a focus will be given to the derivation of prediction models as part of clinical decision support systems, to which machine learning approaches and hybrid imaging can be anchored.

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Section: Machine Learning For Medical Big Data Analysismentioning

confidence: 99%

Section: Machine Learning For Medical Big Data Analysismentioning

confidence: 99%

Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

et al. 2018

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“…Here, our goal is to highlight applications, studies, statistics and products that are derived from the healthcare IoT technological sector. To this purpose, we have followed the methodology presented by [1] and [2], in which the entire IoT sector applied to healthcare has been arranged into five categories and three sub-categories that allow us to identify potential trends. The results of this survey give to the reader a broader view of the state-of-the-art applications and methods used within the healthcare IoT industrial sector and future opportunities of growth.…”

Section: Introductionmentioning

confidence: 99%

Survey on IoT solutions applied to Healthcare

Castro

Coral

Cabra

et al. 2017

DYNA

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The Internet of Things (IoT) is a new technological paradigm that allows any object or thing to be connected to other things, services or people through the Internet. IoT brings tools for empowering working areas such as health, logistics, industry, security, agriculture and environment. In this paper, we introduce a comprehensive survey of IoT technologies, methods, statistics and success cases applied to healthcare. In the last section its talked about the work done in this subject on the Colombian context, including successful applications and current projects.Keywords: Internet of things; e-Health; healthcare.Revisión del estado del arte de soluciones IoT en salud Resumen El internet de las cosas, también conocido como IoT por sus siglas en inglés (Internet of Things), es un nuevo paradigma tecnológico que permite la interconexión de objetos (las cosas), servicios y/o personas por medio de internet. IoT introduce nuevas herramientas que enriquecen el trabajo en diferentes sectores industriales. Este artículo presenta un estudio del trabajo desarrollado en todo el mundo en tecnologías con base en el concepto de IoT en el marco de la industria del cuidado de la salud, incluyendo métodos, estadísticas y casos de éxito. En la última sección, se discute sobre el trabajo realizado en este ámbito en el contexto colombiano, incluyendo aplicaciones exitosas y proyectos que se encuentran en desarrollo.Palabras clave: Internet de las cosas; e Health; cuidado en la salud.

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“…IoT is a rapidly emerging technology that can provide an interface for the communication of information generated by medical equipments over internet [23]. This technology makes a step forward for legacy telehealth systems as no new equipment is required for medical assistance in telehealth systems.…”

Section: Medical Equipments and Internet Of Things (Iot)mentioning

confidence: 99%

Telehealth Technology: Potentials, Challenges and Research Directions for Developing Countries

Raza

Aslam

et al. 2017

6th International Conference on the Development of Biomedical Engineering in Vietnam (BME6)

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Abstract-Telehealth has been developed and successfully applied in clinical practices, gained a strong interest and demonstrated its usefulness for medical diagnosis, treatments and rehabilitation worldwide. The advent of high speed communication technology and complex signal processing techniques, and recent advancements in cloud and cognitive computing, has created a new wave of opportunities for delivering remote healthcare applications and services, where the costeffective diagnosis and treatment solutions as well as healthcare services are important and need to be deployed widely. Nevertheless, there is still a significant challenge in fully adopting this technology due to asymmetry among the healthcare centers, hospitals and the user-ends, especially in developing countries. This paper provides an overview of the telehealth, then to addresses the possible telehealth technologies and applications that could be applied to improve the healthcare service performance, with the focus on the developing countries. The incorporation of different technologies in telehealth including, Internet of Things (IoT), cloud and cognitive computing, medical image processing and effective encoding is introduced and discussed. Finally, the possible research directions, challenges for the efficient telehealth, and potential research and technology collaborations are outlined.

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On the Application of the Internet of Things in the Field of Medical and Health Care

Cited by 112 publications

References 5 publications

Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

Survey on IoT solutions applied to Healthcare

Telehealth Technology: Potentials, Challenges and Research Directions for Developing Countries

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