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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
pandangan teks lengkap
98
Kertas kerja ini menyediakan perspektif untuk perkhidmatan sosial penjagaan kesihatan perubatan masa depan dan perniagaan yang mengintegrasikan teknologi maklumat dan komunikasi (ICT) dan sains data termaju. Pertama, kami mencadangkan platform penjagaan kesihatan perubatan universal yang terdiri daripada rangkaian kawasan badan tanpa wayar (BAN), rangkaian awan dan komputer tepi, pelayan perlombongan data besar dan repositori dengan pembelajaran mesin. Aspek teknikal platform dibincangkan, termasuk keperluan kebolehpercayaan, keselamatan dan keselamatan, iaitu, kebolehpercayaan yang dipanggil. Di samping itu, teknologi baru untuk memenuhi keperluan diperkenalkan. Kemudian penggunaan utama platform untuk perubatan diperibadikan dan pematuhan kawal selia, dan kegunaan sekundernya untuk perniagaan komersial dan operasi mampan dibincangkan. Kami menyasarkan untuk mengendalikan platform penjagaan kesihatan perubatan universal, yang berdasarkan prinsip sains kawal selia, di peringkat serantau dan global. Dalam kertas kerja ini, ujian yang dijalankan di Kanagawa, Jepun dan Oulu, Finland akan didedahkan untuk menggambarkan infrastruktur sosial penjagaan kesihatan perubatan masa depan dengan mengembangkannya ke Asia-Pasifik, Eropah dan seluruh dunia. Kami mewakili aktiviti pusat sains pengawalseliaan peranti perubatan Kanagawa dan cadangan bersama tentang keselamatan dalam platform penjagaan kesihatan perubatan yang boleh dipercayai. Skim baru pemulihan di mana-mana berdasarkan analisis kesan latihan melalui pemantauan jarak jauh aktiviti dan pembelajaran mesin elektrokardiografi (ECG) pesakit dengan rangkaian saraf dicadangkan dan disiasat secara ringkas.
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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Salinan
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
Salinan
@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},}
Salinan
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 -