SU-FF-I-15: Computed Radiography Dose Data Mining and Surveillance as An Ongoing Quality Assurance Improvement Process

2005 ◽  
Vol 32 (6Part3) ◽  
pp. 1907-1907
Author(s):  
B Stewart ◽  
K Kanal ◽  
J Perdue
Keyword(s):  
Data Mining ◽  
Quality Assurance ◽  
Computed Radiography ◽  
Improvement Process ◽  
Ongoing Quality Assurance

Computed Radiography Dose Data Mining and Surveillance as an Ongoing Quality Assurance Improvement Process

2007 ◽  
Vol 189 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Brent K. Stewart ◽  
Kalpana M. Kanal ◽  
James R. Perdue ◽  
Frederick A. Mann
Keyword(s):  
Data Mining ◽  
Quality Assurance ◽  
Computed Radiography ◽  
Improvement Process ◽  
Ongoing Quality Assurance

scholarly journals The Swedish Heart Failure Registry: a living, ongoing quality assurance and research in heart failure

2018 ◽  
Vol 124 (1) ◽  
pp. 65-69 ◽  
Author(s):  
Gianluigi Savarese ◽  
Peter Vasko ◽  
Åsa Jonsson ◽  
Magnus Edner ◽  
Ulf Dahlström ◽  
...  
Keyword(s):  
Heart Failure ◽  
Quality Assurance ◽  
Ongoing Quality Assurance

Digital Marketing and E-Tailing Technological Innovations

2020 ◽  
pp. 37-65
Author(s):  
Alan D. Smith
Keyword(s):  
Data Mining ◽  
Quality Assurance ◽  
Big Data ◽  
Information Retrieval ◽  
Customer Service ◽  
Middle Level ◽  
Purchase Decision ◽  
Product Reviews ◽  
Privacy Concerns ◽  
Web Presence

In an age of public mistrust of the most basic institutions, businesses are not exempted. Essentially all e-tailers want to deliver personalized and real-time communications to customers that are tailored to their interests and preferences, and are based on big data mining that customers will value over privacy concerns. This is an era in which e-commerce retailers continue to dominate the marketplace and it is integral that consumers are able to trust the manufacturers, retailers, and the service/product reviews that they read online. Such trust is particularly important if their ultimate purchase decision is a successful one. A survey of middle-level managers was analyzed to identity the basic elements: e-personalization, namely online purchasing behaviors, personalized communications, information-retrieval services, degree of personal web presence, quality assurance of customer service, and the promotion of customization services. These elements were found to be conceptually and statistically related to retailer benefits of increased buying and customer loyalty.

TU-A-301-10: Pitfalls of Short Term Computed Radiography Mammography Quality Assurance

2011 ◽  
Vol 38 (6Part28) ◽  
pp. 3747-3747
Author(s):  
D Sandova ◽  
P Heintz ◽  
C Kelsey
Keyword(s):  
Quality Assurance ◽  
Computed Radiography ◽  
Short Term

scholarly journals Rational medication use review: a quality assurance/improvement process for HIV/AIDS treatment programme

2015 ◽  
Vol 3 (2) ◽  
pp. 383
Author(s):  
Henry Fomundam ◽  
Andrew Maranga ◽  
Abraham Tesfay ◽  
Lucia Chanetsa ◽  
Vieira Muzola ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Medication Use ◽  
Treatment Programme ◽  
Improvement Process ◽  
Hiv Aids

New Method for Quality Assurance in Computed Radiography

1993 ◽  
Vol 49 (1-3) ◽  
pp. 275-276
Author(s):  
M. Fiebich ◽  
H. Lenzen ◽  
N. Meier ◽  
L. Koetter
Keyword(s):  
Quality Assurance ◽  
Computed Radiography ◽  
New Method

scholarly journals EDUCATIONAL DATA MINING APPROACH FOR ENGINEERING GRADUATE ATTRIBUTES ANALYSIS

2017 ◽  
Author(s):  
Yassine Bouslimani ◽  
Guillaume Durand ◽  
Nabil Belacel
Keyword(s):  
Data Mining ◽  
Factor Model ◽  
Educational Data Mining ◽  
Curriculum Evaluation ◽  
Assessment Process ◽  
Response Patterns ◽  
Past Performance ◽  
Graduate Attributes ◽  
Improvement Process ◽  
Q Matrix

Curriculum improvement and graduate attributes assessments have become recently a serious issue for many Canadian engineering schools. Collecting assessment data concerning graduate attributes and the students’ learning is an important step of curriculum evaluation and the continuous improvement process. To be successful, this improvement process needs appropriate methods and tools for data analysis.Recent developments in the field of Psychometrics and Educational Data Mining (EDM) provide multidimensional item response models able to take into account student and curriculum attributes as parameters. The primary intent of these new models is to predict student successes based on students past performance and the assessment map underlying the tests they completed.We demonstrate in this paper that these models can also be used to analyze the assessment map. In the psychometric and Educational Data mining literature, assessment maps are usually represented as a parameter that associates items to competencies in a matrix called Q-matrix. This concept draws its origins from the Rule-Space Model that was introduced in the eighties to statistically classify student item responses into a set of ideal response patterns associated to different cognitive skills.A method based on the Additive Factor Model has been successfully implemented to analyse the Q-matrix corresponding to the assessment maps used in the graduate assessment process. The results of 17 volunteering anonymous students completing 36 courses at the Université de Moncton between winter 2010 and fall 2015 semesters was analysed with our method. Results obtained provided interesting and useful information regarding the assessment map and the overall assessment process that are presented and discussed in this paper.

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