The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
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102
Cet article fournit des perspectives pour les futurs services sociaux et entreprises de soins médicaux qui intègrent les technologies avancées de l’information et de la communication (TIC) et la science des données. Premièrement, nous proposons une plate-forme universelle de soins de santé composée d'un réseau corporel sans fil (BAN), d'un réseau cloud et d'un ordinateur de pointe, d'un serveur d'exploration de données volumineuses et d'un référentiel avec apprentissage automatique. Les aspects techniques de la plate-forme sont discutés, y compris les exigences de fiabilité, de sûreté et de sécurité, c'est-à-dire ce que l'on appelle la fiabilité. En outre, de nouvelles technologies permettant de satisfaire aux exigences sont introduites. Ensuite, les utilisations principales de la plateforme pour la médecine personnalisée et la conformité réglementaire, ainsi que ses utilisations secondaires pour les affaires commerciales et l'exploitation durable sont discutées. Nous visons à exploiter la plateforme universelle de soins de santé, basée sur le principe de la science réglementaire, aux niveaux régional et mondial. Dans cet article, des essais menés à Kanagawa, au Japon et à Oulu, en Finlande seront révélés pour illustrer une future infrastructure sociale de soins de santé en l'étendant à l'Asie-Pacifique, à l'Europe et au reste du monde. Nous représentons les activités du centre scientifique de réglementation des dispositifs médicaux de Kanagawa et une proposition commune sur la sécurité dans la plateforme fiable de soins de santé médicaux. De nouveaux schémas de réadaptation omniprésente basés sur des analyses de l'effet d'entraînement par surveillance à distance des activités et apprentissage automatique de l'électrocardiographie (ECG) du patient avec un réseau neuronal sont proposés et brièvement étudiés.
Ryuji KOHNO
Yokohama National University (YNU),University of Oulu
Takumi KOBAYASHI
Yokohama National University (YNU)
Chika SUGIMOTO
Yokohama National University (YNU)
Yukihiro KINJO
Yokohama National University (YNU)
Matti HÄMÄLÄINEN
Yokohama National University (YNU),University of Oulu
Jari IINATTI
University of Oulu
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Ryuji KOHNO, Takumi KOBAYASHI, Chika SUGIMOTO, Yukihiro KINJO, Matti HÄMÄLÄINEN, Jari IINATTI, "Medical Healthcare Network Platform and Big Data Analysis Based on Integrated ICT and Data Science with Regulatory Science" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 6, pp. 1078-1087, June 2019, doi: 10.1587/transcom.2018HMI0001.
Abstract: This paper provides perspectives for future medical healthcare social services and businesses that integrate advanced information and communication technology (ICT) and data science. First, we propose a universal medical healthcare platform that consists of wireless body area network (BAN), cloud network and edge computer, big data mining server and repository with machine learning. Technical aspects of the platform are discussed, including the requirements of reliability, safety and security, i.e., so-called dependability. In addition, novel technologies for satisfying the requirements are introduced. Then primary uses of the platform for personalized medicine and regulatory compliance, and its secondary uses for commercial business and sustainable operation are discussed. We are aiming at operate the universal medical healthcare platform, which is based on the principle of regulatory science, regionally and globally. In this paper, trials carried out in Kanagawa, Japan and Oulu, Finland will be revealed to illustrate a future medical healthcare social infrastructure by expanding it to Asia-Pacific, Europe and the rest of the world. We are representing the activities of Kanagawa medical device regulatory science center and a joint proposal on security in the dependable medical healthcare platform. Novel schemes of ubiquitous rehabilitation based on analyses of the training effect by remote monitoring of activities and machine learning of patient's electrocardiography (ECG) with a neural network are proposed and briefly investigated.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018HMI0001/_p
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@ARTICLE{e102-b_6_1078,
author={Ryuji KOHNO, Takumi KOBAYASHI, Chika SUGIMOTO, Yukihiro KINJO, Matti HÄMÄLÄINEN, Jari IINATTI, },
journal={IEICE TRANSACTIONS on Communications},
title={Medical Healthcare Network Platform and Big Data Analysis Based on Integrated ICT and Data Science with Regulatory Science},
year={2019},
volume={E102-B},
number={6},
pages={1078-1087},
abstract={This paper provides perspectives for future medical healthcare social services and businesses that integrate advanced information and communication technology (ICT) and data science. First, we propose a universal medical healthcare platform that consists of wireless body area network (BAN), cloud network and edge computer, big data mining server and repository with machine learning. Technical aspects of the platform are discussed, including the requirements of reliability, safety and security, i.e., so-called dependability. In addition, novel technologies for satisfying the requirements are introduced. Then primary uses of the platform for personalized medicine and regulatory compliance, and its secondary uses for commercial business and sustainable operation are discussed. We are aiming at operate the universal medical healthcare platform, which is based on the principle of regulatory science, regionally and globally. In this paper, trials carried out in Kanagawa, Japan and Oulu, Finland will be revealed to illustrate a future medical healthcare social infrastructure by expanding it to Asia-Pacific, Europe and the rest of the world. We are representing the activities of Kanagawa medical device regulatory science center and a joint proposal on security in the dependable medical healthcare platform. Novel schemes of ubiquitous rehabilitation based on analyses of the training effect by remote monitoring of activities and machine learning of patient's electrocardiography (ECG) with a neural network are proposed and briefly investigated.},
keywords={},
doi={10.1587/transcom.2018HMI0001},
ISSN={1745-1345},
month={June},}
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TY - JOUR
TI - Medical Healthcare Network Platform and Big Data Analysis Based on Integrated ICT and Data Science with Regulatory Science
T2 - IEICE TRANSACTIONS on Communications
SP - 1078
EP - 1087
AU - Ryuji KOHNO
AU - Takumi KOBAYASHI
AU - Chika SUGIMOTO
AU - Yukihiro KINJO
AU - Matti HÄMÄLÄINEN
AU - Jari IINATTI
PY - 2019
DO - 10.1587/transcom.2018HMI0001
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2019
AB - This paper provides perspectives for future medical healthcare social services and businesses that integrate advanced information and communication technology (ICT) and data science. First, we propose a universal medical healthcare platform that consists of wireless body area network (BAN), cloud network and edge computer, big data mining server and repository with machine learning. Technical aspects of the platform are discussed, including the requirements of reliability, safety and security, i.e., so-called dependability. In addition, novel technologies for satisfying the requirements are introduced. Then primary uses of the platform for personalized medicine and regulatory compliance, and its secondary uses for commercial business and sustainable operation are discussed. We are aiming at operate the universal medical healthcare platform, which is based on the principle of regulatory science, regionally and globally. In this paper, trials carried out in Kanagawa, Japan and Oulu, Finland will be revealed to illustrate a future medical healthcare social infrastructure by expanding it to Asia-Pacific, Europe and the rest of the world. We are representing the activities of Kanagawa medical device regulatory science center and a joint proposal on security in the dependable medical healthcare platform. Novel schemes of ubiquitous rehabilitation based on analyses of the training effect by remote monitoring of activities and machine learning of patient's electrocardiography (ECG) with a neural network are proposed and briefly investigated.
ER -