Big Data in Computational Health Informatics

2019 ◽  
pp. 103-142
Author(s):  
Ruogu Fang ◽  
Yao Xiao ◽  
Jianqiao Tian ◽  
Samira Pouyanfar ◽  
Yimin Yang ◽  
...  
Keyword(s):  
Big Data ◽  
2015 ◽  
Vol 19 (10) ◽  
pp. 17-35 ◽  

Amplifying Spatial Awareness via GIS — Tech which brings Healthcare Management, Preventative & Predictive Measures under the same Cloud When it is not just about size, you gotta' be Smart, too! Chew on It! How Singapore-based health informatics company MHC Asia Group crunches big-data to uncover your company's health Digital tool when well-used, it is Passion Carving the Digital Route to Wellness Big Data, Bigger Disease Management and Current preparations to manage the Future Health of Singaporeans A Conversation with Mr Arun Puri Extreme Networks: Health Solutions Big Data in Clinical Research Sector


2017 ◽  
Vol 26 (01) ◽  
pp. 323-325
Author(s):  
C. L. Parra-Calderón ◽  
G. Gómez-Soriano ◽  
J. Galván-Romo ◽  
L. Sáez-Ayerra

2014 ◽  
Vol 23 (01) ◽  
pp. 177-181 ◽  
Author(s):  
W. Hersh ◽  
A. U. Jai Ganesh ◽  
P. Otero

Summary Objective: The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know? Methods: We hypothesize a set of skills that we hope will be discussed among academic and other informaticians. Results: The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one’s area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them. Conclusion: Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in “deep analytical talent” as well as those who need knowledge to support such individuals.


2018 ◽  
Vol 27 (01) ◽  
pp. 234-236 ◽  
Author(s):  
Kwok-Chan Lun

SummaryHealth informatics has benefitted from the development of Info-Communications Technology (ICT) over the last fifty years. Advances in ICT in healthcare have now started to spur advances in Data Technology as hospital information systems, electronic health and medical records, mobile devices, social media and Internet Of Things (IOT) are making a substantial impact on the generation of data. It is timely for healthcare institutions to recognize data as a corporate asset and promote a data-driven culture within the institution. It is both strategic and timely for IMIA, as an international organization in health informatics, to take the lead to promote a data-driven culture in healthcare organizations. This can be achieved by expanding the terms of reference of its existing Working Group on Data Mining and Big Data Analysis to include (1) data analytics with special reference to healthcare, (2) big data tools and solutions, (3) bridging information technology and data technology and (4) data quality issues and challenges.


Author(s):  
Jing Wang ◽  
Zhong-Qiu Zhao ◽  
Xuegang Hu ◽  
Yiu-ming Cheung ◽  
Haibo Hu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document