Optimizing Medical Data Quality Based on Multiagent Web Service Framework

2012 ◽  
Vol 16 (4) ◽  
pp. 745-757 ◽  
Author(s):  
Ching-Seh Wu ◽  
I. Khoury ◽  
H. Shah
Keyword(s):  
Data Quality ◽  
Web Service ◽  
Medical Data ◽  
Service Framework

Discovering Homogenous Service Framework Based on Matching Mechanism and Clustering

2011 ◽  
Vol 341-342 ◽  
pp. 462-466
Author(s):  
Meng Wang ◽  
Shu Yu Li
Keyword(s):  
Web Services ◽  
Web Service ◽  
Search Engine ◽  
Search Space ◽  
Research Direction ◽  
The Internet ◽  
Ongoing Research ◽  
Service Community ◽  
Matching Mechanism ◽  
Service Framework

How to efficiently select Web services that can best meet the requirements of consumers is an ongoing research direction in Web service community. However, current discovery systems support either WSDL or OWL-S Web services but not both.Through the automatically collected WSDL files and the OWL-S web service related matching mechanism, the idea of transforming various existing web services on the Internet into a service cluster of similar homogeneous , then we can create a service search engine successfully and at the same time the search space can be reduced. By means of providing a mechanism for matching the characteristics properties of relevant web services, we can put them all together into a group which can be found and applied.

A Light Mobile Web Service Framework Based on Axis2

2013 ◽  
pp. 977-985 ◽  
Author(s):  
Zhun Shen ◽  
Ka Lok Man ◽  
Hai-Ning Liang ◽  
Nan Zhang ◽  
Charles Fleming ◽  
...  
Keyword(s):  
Web Service ◽  
Mobile Web ◽  
Service Framework

Medical data quality assessment: On the development of an automated framework for medical data curation

2019 ◽  
Vol 107 ◽  
pp. 270-283 ◽  
Author(s):  
Vasileios C. Pezoulas ◽  
Konstantina D. Kourou ◽  
Fanis Kalatzis ◽  
Themis P. Exarchos ◽  
Aliki Venetsanopoulou ◽  
...  
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Medical Data ◽  
Data Curation ◽  
Data Quality Assessment

An SOA-Based Architecture to Share Medical Data with Privacy Preservation

2011 ◽  
Vol 2 (3) ◽  
pp. 11-26
Author(s):  
Mahmoud Barhamgi ◽  
Djamal Benslimane ◽  
Chirine Ghedira ◽  
Brahim Medjahed
Keyword(s):  
Web Services ◽  
Web Service ◽  
Data Sharing ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Medical Data ◽  
Query Rewriting ◽  
Healthcare Organizations ◽  
Privacy Constraints ◽  
Viable Approach

Recent years have witnessed a growing interest in using Web services as a reliable means for medical data sharing inside and across healthcare organizations. In such service-based data sharing environments, Web service composition emerged as a viable approach to query data scattered across independent locations. Patient data privacy preservation is an important aspect that must be considered when composing medical Web services. In this paper, the authors show how data privacy can be preserved when composing and executing Web services. Privacy constraints are expressed in the form of RDF queries over a mediated ontology. Query rewriting algorithms are defined to process those queries while preserving users’ privacy.

A web service framework for astronomical remote observation in Antarctica by using satellite link

2018 ◽  
Vol 24 ◽  
pp. 17-24 ◽  
Author(s):  
M.-h. Jia ◽  
Y.-q. Chen ◽  
G.-y. Zhang ◽  
P. Jiang ◽  
H. Zhang ◽  
...  
Keyword(s):  
Web Service ◽  
Satellite Link ◽  
Remote Observation ◽  
Service Framework

Application of Big data scientific research analysis platform in clinical medical research

2021 ◽  
pp. 1-12
Author(s):  
Jing Wang ◽  
Jie Wei ◽  
Long Li ◽  
Lijian Zhang
Keyword(s):  
Big Data ◽  
Drug Discovery ◽  
Data Quality ◽  
Sample Size ◽  
Real World ◽  
Medical Data ◽  
Large Sample Size ◽  
Research Implementation ◽  
Large Sample ◽  
Application Systems

With the rapid development of evidence-based medicine, translational medicine, and pharmacoeconomics in China, as well as the country’s strong commitment to clinical research, the demand for physicians’ research continues to increase. In recent years, real-world studies are attracting more and more attention in the field of health care, as a method of post-marketing re-evaluation of drugs, RWS can better reflect the effects of drugs in real clinical settings. In the past, it was difficult to ensure data quality and efficiency of research implementation because of the large sample size required and the large amount of medical data involved. However, due to the large sample size required and the large amount of medical data involved, it is not only time-consuming and labor-intensive, but also prone to human error, making it difficult to ensure data quality and efficiency of research implementation. This paper analyzes and summarizes the existing application systems of big data analytics platforms, and concludes that big data research analytics platforms using natural language processing, machine learning and other artificial intelligence technologies can help RWS to quickly complete the collection, integration, processing, statistics and analysis of large amounts of medical data, and deeply mine the intrinsic value of the data, real-world research in new drug development, drug discovery, drug discovery, drug discovery, and drug discovery. It has a broad application prospect for multi-level and multi-angle needs such as economics, medical insurance cost control, indications/contraindications evaluation, and clinical guidance.

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