Data exchanges based on blockchain in m-Health applications

被引:17
作者
Clim, Antonio [1 ]
Zota, Razvan Daniel [1 ]
Constantinescu, Radu [1 ]
机构
[1] Bucharest Univ Econ Studies, 15-17 Dorobanti, Bucharest 010552, Romania
来源
10TH INT CONF ON EMERGING UBIQUITOUS SYST AND PERVAS NETWORKS (EUSPN-2019) / THE 9TH INT CONF ON CURRENT AND FUTURE TRENDS OF INFORMAT AND COMMUN TECHNOLOGIES IN HEALTHCARE (ICTH-2019) / AFFILIATED WORKOPS | 2019年 / 160卷
关键词
mobile healthcare; blockchain technology; data exchange; machine-learning algorithms;
D O I
10.1016/j.procs.2019.11.088
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The most important aspect of handling data in the healthcare industry is its seamless and secure transition across intercepting nodes. Effective elimination of third-party entities and ensuring direct links between patient and healthcare provider can result in the transmission of error-free, unduplicated data. The use of blockchains can open up opportunities to counter the current requirements due to their ability to safely share information across nodes and networks from the access point and secure the safety of transactions. Currently, sharing medical data is observed to be slow, incomplete, insecure, and provider-centric. These shortcomings prevent data interoperability and are a consequence of lack of foundational, structural, and semantic inoperability. By applying the blockchain technologies with appropriate markers, the safety of patient data can be ensured during data transmission. This paper evaluates the potential use of blockchain technology in association with mobile-based healthcare applications. (C) 2019 The Authors. Published by Elsevier B.V.
引用
收藏
页码:281 / 288
页数:8
相关论文
共 20 条
[1]  
[Anonymous], 2016, ONCNIST USE BLOCKCHA
[2]  
[Anonymous], IDC iView: IDC Analyze the future
[3]  
Boulos Maged N Kamel, 2014, Online J Public Health Inform, V5, P229, DOI 10.5210/ojphi.v5i3.4814
[4]   New technologies in predicting, preventing and controlling emerging infectious diseases [J].
Christaki, Eirini .
VIRULENCE, 2015, 6 (06) :554-561
[5]  
Clim Antonio, 2019, Informatica Economica, V23, P50, DOI 10.12948/issn14531305/23.1.2019.05
[6]   Effectiveness, acceptability and usefulness of mobile applications for cardiovascular disease self-management: Systematic review with meta-synthesis of quantitative and qualitative data [J].
Coorey, Genevieve M. ;
Neubeck, Lis ;
Mulley, John ;
Redfern, Julie .
EUROPEAN JOURNAL OF PREVENTIVE CARDIOLOGY, 2018, 25 (05) :505-521
[7]  
delRosario M., 2015, SENSORS, V15
[8]   SQL and data analysis. Some implications for data analysits and higher education [J].
Fotache, Marin ;
Strimbei, Catalin .
GLOBALIZATION AND HIGHER EDUCATION IN ECONOMICS AND BUSINESS ADMINISTRATION - GEBA 2013, 2015, 20 :243-251
[9]   Machine Learning and Data Mining Methods in Diabetes Research [J].
Kavakiotis, Ioannis ;
Tsave, Olga ;
Salifoglou, Athanasios ;
Maglaveras, Nicos ;
Vlahavas, Ioannis ;
Chouvarda, Ioanna .
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2017, 15 :104-116
[10]  
Leslie I., 2011, Mobile communications for medical care: A study of current and future healthcare and health promotion applications, and their use in China and elsewhere