scholarly journals Big Data Application in Biomedical Research and Health Care: A Literature Review

2016 ◽  
Vol 8 ◽  
pp. BII.S31559 ◽  
Author(s):  
Jake Luo ◽  
Min Wu ◽  
Deepika Gopukumar ◽  
Yiqing Zhao
Keyword(s):  
Public Health ◽  
Health Care ◽  
Big Data ◽  
Health Informatics ◽  
Imaging Informatics ◽  
Clinical Informatics ◽  
Public Health Informatics ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.

scholarly journals Federated Learning in Big Data Application and Sharing

2020 ◽  
Author(s):  
Jing Yang ◽  
Quan Zhang ◽  
Kunpeng Liu ◽  
Peng Jin ◽  
Guoyi Zhao
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
The State ◽  
Ideal Model ◽  
Local Data ◽  
Data Safety ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application ◽  
Uniform Model

In recent years, electricity big data has extensive applications in the grid companies across the provinces. However, certain problems are encountered including, the inability to generate an ideal model using the isolated data possessed by each company, and the priority concerns for data privacy and safety during big data application and sharing. In this pursuit, the present research envisaged the application of federated learning to protect the local data, and to build a uniform model for different companies affiliated to the State Grid. Federated learning can serve as an essential means for realizing the grid-wide promotion of the achievements of big data applications, while ensuring the data safety.

scholarly journals Clinical Informatics Board Certification: History, Current Status, and Predicted Impact on the Clinical Informatics Workforce

2010 ◽  
Vol 01 (01) ◽  
pp. 11-18 ◽  
Author(s):  
Don Detmer ◽  
Benson Munger ◽  
Christoph Lehmann
Keyword(s):  
Public Health ◽  
Medical Informatics ◽  
Health Informatics ◽  
Policy Design ◽  
Clinical Care ◽  
Work Force ◽  
Clinical Informatics ◽  
Current Status ◽  
Public Health Informatics ◽  
Medical Specialties

SummaryWithin health and health care, medical informatics and its subspecialties of biomedical, clinical, and public health informatics have emerged as a new discipline with increasing demands for its own work force. Knowledge and skills in medical informatics are widely acknowledged as crucial to future success in patient care, research relating to biomedicine, clinical care, and public health, as well as health policy design. The maturity of the domain and the demand on expertise necessitate standardized training and certification of professionals. The American Medical Informatics Association (AMIA) embarked on a major effort to create professional level education and certification for physicians of various professions and specialties in informatics. This article focuses on the AMIA effort in the professional structure of medical specialization, e.g., the American Board of Medical Specialties (ABMS) and the related Accreditation Council for Graduate Medical Education (ACGME). This report summarizes the current progress to create a recognized sub-certificate of competence in Clinical Informatics and discusses likely near term (three to five year) implications on training, certification, and work force with an emphasis on clinical applied informatics.

scholarly journals Exploration on the Construction of Sharing Platform of Power Big Data Application

2020 ◽  
Author(s):  
Jing Yang ◽  
Quan Zhang ◽  
Lihua Gong ◽  
Longzhu Zhu ◽  
Kunpeng Liu
Keyword(s):  
Big Data ◽  
Big Data Applications ◽  
Data Application ◽  
Application Sharing ◽  
Big Data Application

Big data application sharing supermarket is a big data application sharing portal. The first, one or more enterprise users can share and use the same big data application product. This product comes from the contribution of enterprise users of a certain sharing supermarket. In this way, we can solve the problem of unbalanced development of big data capabilities, and avoid repeated construction and repeated investment in the same kind of big data applications; the second. Through such a sharing platform, many enterprises carry out cooperation such as federal learning to jointly create big data application products.

Database Systems for Big Data Storage and Retrieval

2018 ◽  
pp. 76-100 ◽  
Author(s):  
Venkat Gudivada ◽  
Amy Apon ◽  
Dhana L. Rao
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Database Systems ◽  
Query Languages ◽  
Research Issues ◽  
Storage And Retrieval ◽  
Emerging Trends ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application

Special needs of Big Data applications have ushered in several new classes of systems for data storage and retrieval. Each class targets the needs of a category of Big Data application. These systems differ greatly in their data models and system architecture, approaches used for high availability and scalability, query languages and client interfaces provided. This chapter begins with a description of the emergence of Big Data and data management requirements of Big Data applications. Several new classes of database management systems have emerged recently to address the needs of Big Data applications. NoSQL is an umbrella term used to refer to these systems. Next, a taxonomy for NoSQL systems is developed and several NoSQL systems are classified under this taxonomy. Characteristics of representative systems in each class are also discussed. The chapter concludes by indicating the emerging trends of NoSQL systems and research issues.

scholarly journals The Application of “Big Data Analysis + Hierarchical Medical” Model in the Context of the COVID-19

2021 ◽  
Vol 292 ◽  
pp. 02014
Author(s):  
Xingyu Yang ◽  
Tianyu Yan ◽  
Zelong Huang ◽  
Xiaofang Zhang ◽  
Yuchen Zhao ◽  
...  
Keyword(s):  
Public Health ◽  
Big Data ◽  
Data Analysis ◽  
Medical Model ◽  
Big Data Analysis ◽  
Public Health Emergencies ◽  
Data Application ◽  
The World ◽  
Big Data Application ◽  
Hierarchical Medical System

The COVID-19 epidemic has swept the world, causing serious impact and influence on economic development and residents' life in countries all over the world. This paper takes China as an example, further analyses the characteristics of China's hierarchical medical model based on the international hierarchical medical research planning, and proposes the application of “big data analysis + hierarchical medical” model for the new coronavirus epidemic and other public health emergencies based on the advantages of big data application to solve public health crises, in order to provide a reference for the planning of hierarchical medical system during the epidemic. It is expected to provide reference for the planning of hierarchical medical and health system during the epidemic, which is an innovative attempt of the medical industry.

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