Title
Medical Healthcare Network Platform And Big Data Analysis Based On Integrated Ict And Data Science With Regulatory Science
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.
Year
DOI
Venue
2019
10.1587/transcom.2018HMI0001
IEICE TRANSACTIONS ON COMMUNICATIONS
Keywords
Field
DocType
medical ICT, body area network (BAN), medical healthcare, big data, machine learning, dependability, regulatory science
Data science,Health care,Dependability,Computer science,Regulatory science,Information and Communications Technology,Big data
Journal
Volume
Issue
ISSN
E102B
6
0916-8516
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Ryuji Kohno1747623.24
Ryuji Kohno2747623.24
Takumi Kobayashi324131.18
Sugimoto, C.487.06
Yukihiro Kinjo500.34
Matti Hämäläinen616014.05
Jari Iinatti715033.33