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Data Quality and Completeness in a Web Stroke Registry as the Basis for Data and Process Mining

Giordano Lanzola, Enea Parimbelli, Giuseppe Micieli, Anna Cavallini, Silvana Quaglini
2014 Journal of Healthcare Engineering  
Finally we report on some statistics, such as calculation of indicators for assessing the quality of stroke care, data mining for knowledge discovery, and process mining for comparing different processes  ...  The most important results of the re-engineering are an improved user experience with data entry, and a definitely better data quality that guarantees the reliability of data analyses.  ...  We thank all the participants to the SUN network for providing stroke patients data.  ... 
doi:10.1260/2040-2295.5.2.163 pmid:24918182 fatcat:zdlvul4jovdv3hlxp7y36ztbfy

Statistical Summary of Ground-Water-Quality Data From Selected Mined Areas in the Powder River Basin, Wyoming

D. Naftz, M. Martin
1987 Journal American Society of Mining and Reclamation  
Water-quality samples were obtained from 144 wells completed in either the coal aquifers (premining water) or spoil aquifers (postmining water) ·St -10 _s:urface coal. mines •.  ...  Analytical data for more than 650 water-quality samples were statisticaily analyzed.  ...  Water-quality samples were obtained from 144 wells completed in either the coal aquifers (premining water) or spoil aquifers (postmining water) ·St -10 _s:urface coal. mines •.  ... 
doi:10.21000/jasmr87010133 fatcat:styula4lnzd7fbwjknslijcgqm

The Effects and Interactions of Data Quality and Problem Complexity on Classification

Roger Blake, Paul Mangiameli
2011 Journal of Data and Information Quality  
Data quality remains a persistent problem in practice and a challenge for research. In this study  ...  Our research can be extended in several ways. Interaction effects between the four data quality dimensions themselves warrant investigation.  ...  in determining how efforts to improve data quality should be prioritized and how it affects data mining.  ... 
doi:10.1145/1891879.1891881 dblp:journals/jdiq/BlakeM11 fatcat:u4ue3v37hbb25lxbllc6zfsurm


Che McRae, Ken DeVos
2006 Journal American Society of Mining and Reclamation  
While many countries and international organizations have specific regulations for mining effluent and receiving water quality, the cause-and-effect link between mine wastes and the surrounding environment  ...  In an ideal world, the project would be delayed until sufficient data have been gathered to answer all pertinent questions.  ...  When proper baseline geochemistry and water quality data is collected and proper evaluations are completed during the project planning phase, mitigation measures can often be implemented in the design  ... 
doi:10.21000/jasmr06021250 fatcat:6a3uuda2wnbtzl6j3erpynk3wm

Course planning of higher education to meet market demand by using data mining techniques– a case of a Technical University in India

C. Usharani, Rm. Chandrasekaran
2010 Journal of clean energy technologies  
Data mining techniques are used to analyze the course preferences and course completion rates of enrollees in different Institutions in a Technical University.  ...  Records of enrollees from 2007-09 were then analyzed by three data mining algorithms: Decision Tree, Link Analysis, and Decision Forest.  ...  How the factors determining the quality of education using data mining techniques.  ... 
doi:10.7763/ijcte.2010.v2.245 fatcat:mlaeny3nq5hzpcf4s5ufyofyqu

Data mining of graduation project selection database

Wu Xie, Huimin Zhang, Bizhong Wei, Guanghai Fang
2011 Procedia Engineering  
The information system was data mined with ID3 algorithm, and a decision tree is gained for researching these graduation projects choices.  ...  In order to improve the quality of graduate project, a database system of hundreds of graduation project selection results was established in C# language of Visual Studio.  ...  data mining.  ... 
doi:10.1016/j.proeng.2011.08.751 fatcat:c4varcrwvbgqhksoxyysrrd4ja

Use Data Mining Cleansing to Prepare Data for Strategic Decisions [chapter]

Mawande Sikibi
2022 Artificial Intelligence  
Pre-processing data on the dataset is often neglected, but it is an important step in the data mining process.  ...  Despite the importance of data collection, data quality remains a pervasive and thorny challenge in almost any production organization.  ...  Acknowledgements First, I would like to thank God for His blessing in completing this paper and my highest gratitude goes to my mentor for guarding me throughout this paper.  ... 
doi:10.5772/intechopen.99144 fatcat:vvu6ayw5a5ex7bkhmhzwzozpry

Toward objective software process information: experiences from a case study

Jana Samalikova, Rob Kusters, Jos Trienekens, Ton Weijters, Paul Siemons
2010 Software quality journal  
The goal of process mining is to better understand the development processes, to compare constructed process models with the 'official' guidelines and procedures in quality manuals and, subsequently, to  ...  This paper reports on process mining case studies in a large industrial company in The Netherlands. The subject of the process mining is a particular process: the change control board (CCB) process.  ...  Process mining strongly depends on the quality of collected and stored data, and a quite large number of process instances in the available data sets had to be filtered out due to incompleteness.  ... 
doi:10.1007/s11219-010-9105-8 fatcat:rpdp6vyxbnfgnjhldvv6qrcqqi

The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database

Angelina Prima Kurniati, Eric Rojas, David Hogg, Geoff Hall, Owen A Johnson
2018 Health Informatics Journal  
Our paper aims to: (i) explore data quality issues for healthcare process mining using MIMIC-III, (ii) provide a structured assessment of MIMIC-III data quality and challenge for process mining, and (iii  ...  There is a growing body of literature on process mining in healthcare.  ...  Can the MIMIC-III database be used to better understand data quality issues for process mining in healthcare? Q2. What are the data quality issues for process mining with MIMIC-III? Q3.  ... 
doi:10.1177/1460458218810760 pmid:30488750 fatcat:3idg3fkutrg5rn2mueiov7x3ta

Leveraging Data Quality to Better Prepare for Process Mining: An Approach Illustrated Through Analysing Road Trauma Pre-Hospital Retrieval and Transport Processes in Queensland

Robert Andrews, Moe Wynn, Kirsten Vallmuur, Arthur ter Hofstede, Emma Bosley, Mark Elcock, Stephen Rashford
2019 International Journal of Environmental Research and Public Health  
quality issues can be exploited in the planning, data extraction and log building phases of any process mining analysis, (iii) do not highlight potential impacts of poor quality data on different types  ...  While noting the importance of data quality, existing process mining methodologies (i) do not provide details on how to assess the quality of event data (ii) do not consider how the identification of data  ...  a before b a " b a after Milestone Activities Pre-Study Process Mining Analysis In this section we complete the quality analysis by (i) generating event logs from the sample respective data sets  ... 
doi:10.3390/ijerph16071138 pmid:30934913 pmcid:PMC6479847 fatcat:3rnyjl4dfbhzjl7gasemcqkxpm

Predicting water quality associated with land cover change in the Grootdraai Dam catchment, South Africa

Anja du Plessis, Tertius Harmse, Fethi Ahmed
2015 Water international  
Intricate relationships between land cover and specific water quality parameters were quantified and unique model equations were formulated to predict water quality in the region.  ...  Urban and mining developments should be re-evaluated due to the accompanied significant hydrological consequences.  ...  Acknowledgements The authors would like to thank the South African Weather Service for rainfall data, the Department of Water Affairs for evaporation and water flow data, Rand Water for water quality data  ... 
doi:10.1080/02508060.2015.1067752 fatcat:zp6incbcubhwrlajnzl3rgguy4

Decision analysis of data mining project based on Bayesian risk

Guangli Nie, Lingling Zhang, Ying Liu, Xiuyu Zheng, Yong Shi
2009 Expert systems with applications  
Based on the Bayesian risk, we build a model taking the risk attitude of the top executive in account to help them make decision whether to do data mining or not.  ...  This paper discusses the factors affect the data mining project.  ...  The total score of the data quality is defined in Eq. (1): S quality ¼ ðs accuracy þ s timeliness þ s completeness þ s consistency þ s years Þ=5 ð1Þ Human and finance factors Data mining projects can  ... 
doi:10.1016/j.eswa.2008.05.014 fatcat:nhhhcu6itbh5fkh4yyymaphfom

A General Approach to Mining Quality Pattern-Based Clusters from Microarray Data [chapter]

Daxin Jiang, Jian Peii, Aidong Zhang
2005 Lecture Notes in Computer Science  
In this paper, we address the above two problems by proposing a general quality-driven approach to mining top-k quality pattern-based clusters.  ...  Pattern-based clustering has broad applications in microarray data analysis, customer segmentation, e-business data analysis, etc.  ...  Introduction Clustering is an important data mining problem.  ... 
doi:10.1007/11408079_18 fatcat:xrphod7f3rda3gt55xtndvqywu

investigation of source code mining using novel code mining parameter matrix: recent state of art

2016 International Journal of Latest Trends in Engineering and Technology  
The researchers have demonstrated the successful use of data mining algorithms to find the rules from existing projects to improve the quality of the software development in the new project.  ...  Thus various research outcomes of data mining techniques [1] are been deployed to detect software quality and development productivity.  ... 
doi:10.21172/1.73.512 fatcat:k2s6xgwamff2xcas4ck7az4xse

Mining Mass Spectrometry Quality Control Data

Wout Bittremieux, Pieter Kelchtermans, Dirk Valkenborg, Lennart Martens, Bart Goethals, Kris Laukens
2014 Zenodo  
In addition, by making use of data mining and machine learning approaches, several advanced analyses can be performed between different mass spectrometry runs as well.  ...  Mining mass spectrometry quality control data Introduction Because of the inherent complexity of mass spectrometry, the results of an experiment can be subject to a large variability.  ...  Quality control data mining Quality control samples are standard samples that are periodically run to asses the performance of a mass spectrometry instrument.  ... 
doi:10.5281/zenodo.55988 fatcat:6zrf6qmjwnhurirnd6iueah77u
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