Intelligent, Secure Big Health Data Management Using Deep Learning and Blockchain Technology: An Overview

2019 ◽  
pp. 187-209 ◽  
Author(s):  
Sohail Saif ◽  
Suparna Biswas ◽  
Samiran Chattopadhyay
Keyword(s):  
Deep Learning ◽  
Data Management ◽  
Health Data ◽  
Blockchain Technology

scholarly journals Having Our “Omic” Cake and Eating It Too?: Evaluating User Response to Using Blockchain Technology for Private and Secure Health Data Management and Sharing

2021 ◽  
Vol 3 ◽  
Author(s):  
Victoria L. Lemieux ◽  
Darra Hofman ◽  
Hoda Hamouda ◽  
Danielle Batista ◽  
Ravneet Kaur ◽  
...  
Keyword(s):  
Data Management ◽  
Health Data ◽  
Healthcare Research ◽  
Social Data ◽  
Cognitive Constraints ◽  
Healthcare Data ◽  
Blockchain Technology ◽  
The Social ◽  
Technical Issues ◽  
Careful Design

This paper reports on end users' perspectives on the use of a blockchain solution for private and secure individual “omics” health data management and sharing. This solution is one output of a multidisciplinary project investigating the social, data, and technical issues surrounding application of blockchain technology in the context of personalized healthcare research. The project studies potential ethical, legal, social, and cognitive constraints of self-sovereign healthcare data management and sharing, and whether such constraints can be addressed through careful design of a blockchain solution.

Applying Blockchain Technologies in Healthcare

2020 ◽  
pp. 69-92
Author(s):  
Zehra Ozge Candereli ◽  
Serhat Burmaoglu ◽  
Levent B. Kidak ◽  
Dilek Ozdemir Gungor
Keyword(s):  
Clinical Trials ◽  
Data Management ◽  
Health Data ◽  
Digital Identity ◽  
Payment Systems ◽  
Privacy And Security ◽  
Security Issues ◽  
Blockchain Technology ◽  
Application Fields ◽  
The Web

Recently, one of the inventive developments penetrating many industries is blockchain technology. In the era of globalization and digitalization, blockchain has garnered interest in various application fields from health data management to clinical trials. In this study, we aimed to explore blockchain applications in healthcare with an explorative perspective with a scientometrics analysis. With this analysis, the trends and evolutionary relations between health and blockchain technology were examined via the queries in the Web of Science database. In the analysis, the author keyword co-occurrences were used for demonstrating concept relationships. To understand the new emerging study field, VosViewer was used for network visualizations and CiteSpace free java-based software was used for scientometrics analysis. As a result, it can be implied that the main focus areas of the studies on blockchain are solving payment systems, digital identity, and privacy and security issues in healthcare field.

Deep learning based Blockchain solution for preserving privacy in future vehicles

2020 ◽  
pp. 1-14
Author(s):  
Varsha R ◽  
Meghna Manoj Nair ◽  
Siddharth M. Nair ◽  
Amit Kumar Tyagi
Keyword(s):  
Deep Learning ◽  
Autonomous Vehicles ◽  
Recommendation System ◽  
Privacy Preserving ◽  
Smart Devices ◽  
The Road ◽  
Blockchain Technology ◽  
Technological Advances ◽  
Previous Decade ◽  
Smart Things

The Internet of Things (smart things) is used in many sectors and applications due to recent technological advances. One of such application is in the transportation system, which is of primary use for the users to move from one place to another place. The smart devices which were embedded in vehicles are useful for the passengers to solve his/her query, wherein future vehicles will be fully automated to the advanced stage, i.e. future cars with driverless feature. These autonomous cars will help people a lot to reduce their time and increases their productivity in their respective (associated) business. In today’s generation and in the near future, privacy preserving and trust will be a major concern among users and autonomous vehicles and hence, this paper will be able to provide clarity for the same. Many attempts in previous decade have provided many efficient mechanisms, but they all work only with vehicles along with a driver. However, these mechanisms are not valid and useful for future vehicles. In this paper, we will use deep learning techniques for building trust using recommender systems and Blockchain technology for privacy preserving. We also maintain a certain level of trust via maintaining the highest level of privacy among users living in a particular environment. In this research, we developed a framework that could offer maximum trust or reliable communication to users over the road network. With this, we also preserve privacy of users during traveling, i.e., without revealing identity of respective users from Trusted Third Parties or even Location Based Service in reaching a destination. Thus, Deep Learning based Blockchain Solution (DLBS) is illustrated for providing an efficient recommendation system.

scholarly journals BLOCKCHAIN TECHNOLOGY IMPLEMENTATION ON MEDICAL RECORDS DATA MANAGEMENT: A REVIEW OF RECENT STUDIES

2020 ◽  
Vol 9 (2) ◽  
pp. 107-112
Author(s):  
Dian Budi Santoso ◽  
Anis Fuad ◽  
Guntur Budi Herwanto ◽  
Ahmad Watsiq Maula
Keyword(s):  
Data Management ◽  
Medical Records ◽  
Technology Implementation ◽  
Technology Infrastructure ◽  
Scientific Publications ◽  
Digital Currency ◽  
Blockchain Technology ◽  
Research Article ◽  
Full Control ◽  
Currency Management

Blockchain first introduced and implemented in digital currency management and transactions. Its application to medical records data management is a novelty. This paper described the implementation of blockchain technology in the healthcare industry, especially in medical records data management A literature review was conducted on three popular databases, ScienceDirect, SpringerLink, and IEEE Xplore with the keywords "health", "medical record" and "blockchain" with "research article" and "conference proceeding" filters. There are a few articles that meet the criteria to review indicated that the implementation of blockchain technology in medical records data management is a novelty and still in the early phase. Blockchain is a potential technology in supporting the implementation of electronic medical records, especially related to data integration and privacy. Several scientific publications related to the implementation of blockchain for medical records data management shown that the implementation of this technology will make the patient have full control over their health data. Yet there are still many challenges in the implementation both from the user side and the technology infrastructure.

scholarly journals Data Lakes and Data Visualization: An Innovative Approach to Addressing the Many Challenges of Health Workforce Planning

2015 ◽  
Vol 7 (3) ◽  
Author(s):  
Denise D. Krause
Keyword(s):  
Data Management ◽  
Data Visualization ◽  
Health Workforce ◽  
Health Planning ◽  
Workforce Planning ◽  
Health Data ◽  
Primary Objective ◽  
The State ◽  
Data Repository ◽  
Health Workforce Planning

Background: There are a variety of challenges to health workforce planning, but access to data is critical for effective evidence-based decision-making. Many agencies and organizations throughout Mississippi have been collecting quality health data for many years. Those data have historically resided in data silos and have not been readily shared. A strategy was developed to build and coordinate infrastructure, capacity, tools, and resources to facilitate health workforce and population health planning throughout the state.Objective: Realizing data as the foundation upon which to build, the primary objective was to develop the capacity to collect, store, maintain, visualize, and analyze data from a variety of disparate sources -- with the ultimate goal of improving access to health care.Specific aims were to:1)  build a centralized data repository and scalable informatics platform,2)  develop a data management solution for this platform and then,3)  derive value from this platform by facilitating data visualization and analysis.Methods: We designed and constructed a managed data lake for health data from disparate sources throughout the state of Mississippi. A data management application was developed to log and track all data sources, maps and geographies, and data marts.  With this informatics platform as a foundation, we use a variety of tools to visualize and analyze data.Results: Samples of data visualizations that aim to inform health planners and policymakers are presented. Many agencies and organizations throughout the state benefit from this platform.Conclusion: The overarching goal is that by providing timely, reliable information to stakeholders, Mississippians in general will experience improved access to quality care. 

scholarly journals Applying deep learning for adverse pregnancy outcome detection with pre-pregnancy health data

2018 ◽  
Vol 189 ◽  
pp. 10014 ◽  
Author(s):  
Yu Mu ◽  
Kai Feng ◽  
Ying Yang ◽  
Jingyuan Wang
Keyword(s):  
Deep Learning ◽  
Pregnancy Outcome ◽  
Pregnancy Outcomes ◽  
Learning Algorithm ◽  
Adverse Pregnancy Outcome ◽  
Health Data ◽  
Adverse Pregnancy Outcomes ◽  
Deep Learning Algorithm ◽  
Adverse Pregnancy

Adverse pregnancy outcomes can bring enormous losses to both families and the society. Thus, pregnancy outcome prediction stays a crucial research topic as it may help reducing birth defect and improving the quality of population. However, recent advances in adverse pregnancy outcome detection are driven by data collected after mothers having been pregnant. In this situation, if a bad pregnancy outcome is diagnosed, the parents will suffer both physically and emotionally. In this paper, we develop a deep learning algorithm which is able to detect and classify adverse pregnancy outcomes before parents getting pregnant. We train a multi-layer neural network by using a dataset of 75542 couples’ multidimension pre-pregnancy health data. Our model outperforms some of algorithms in accuracy, recall and F1 score.

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