Data quality analysis of the station of geological and technological researches in recognizing losses and kicks to improve the prediction accuracy of neural network algorithms

2020 ◽  
pp. 63-67 ◽  
Author(s):  
A.I. Arkhipov ◽  
◽  
A.N. Dmitrievsky ◽  
N.A. Eremin ◽  
A.D. Chernikov ◽  
...  
Keyword(s):  
Neural Network ◽  
Data Quality ◽  
Prediction Accuracy ◽  
Quality Analysis ◽  
Network Algorithms ◽  
Data Quality Analysis

A Field case of data quality analysis

1996 ◽  
Author(s):  
B. C. Scheffers ◽  
E. C. C. Wildeboer Schut ◽  
J. A. C. Meekes ◽  
H. L. H. Cox
Keyword(s):  
Data Quality ◽  
Quality Analysis ◽  
Field Case ◽  
Data Quality Analysis

scholarly journals Data Quality Methods and Applications in Health Care System: A Systematic Literature Review

2019 ◽  
Vol 14 (4) ◽  
pp. 35 ◽  
Author(s):  
Paolo Pietro Biancone ◽  
Silvana Secinaro ◽  
Valerio Brescia ◽  
Davide Calandra
Keyword(s):  
Data Quality ◽  
English Language ◽  
Business Management ◽  
Quantitative Information ◽  
Quality Analysis ◽  
Statistical Control ◽  
Use Of Data ◽  
System A ◽  
Language Of Publication ◽  
Data Quality Analysis

The use of data cataloging tools allows keeping different records of both qualitative and quantitative information. However, the large amount of data is not always synonymous with quality, in the medical field this argument becomes even more critical if it is considered the consequences that the lack of a systematic and rigorous process can have for patients. The analysis was conducted through a systematic review includes several general cases and practical methodologies of data quality analysis in the health context. The search for results was made using the keywords "data quality" and "health." The study considers publications made from 2014 to 2018, topic related to Business, Management and Accounting, exclusively in the case of the Tutto platform peer-review journals were chosen, English language of publication. Efficient use of information requires databases that can collect and order health information. However, this is the first step, data quality attempts to go further through the creation of qualitative or statistical control processes and indicators able to ascertain the lack of data or identify potential anomalies. The conducted analysis sets the stage for future quality implementation in the clinical pathway and patient management.

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