The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Enhancement of Data Quality in Health Care Industry: A Promising Data Quality Approach
|
|
Author(s): Asmaa S. Abdo (Menoufia University, Egypt), Rashed K. Salem (Menoufia University, Egypt)and Hatem M. Abdul-Kader (Menoufia University, Egypt)
Copyright: 2017
Pages: 21
Source title:
Handbook of Research on Machine Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt)and Tarek Gaber (Suez Canal University, Egypt)
DOI: 10.4018/978-1-5225-2229-4.ch011
Purchase
|
Abstract
Ensuring data quality is a growing challenge, particularly when emerging big data applications. This chapter highlights data quality concepts, terminologies, techniques, as well as research issues. Recent studies have shown that databases are often suffered from inconsistent data, which ought to be resolved in the cleaning process. Data mining techniques can play key role for ensuring data quality, which can be reutilized efficiently in data cleaning process. In this chapter, we introduce an approach for dependably generating rules from databases themselves autonomously, in order to detect data inconsistency problems from large databases. The proposed approach employs confidence and lift measures with integrity constraints to guarantee that generated rules are minimal, non-redundant and precise. Since healthcare applications are critical, and managing healthcare environments efficiently results in patient care improvement. The proposed approach is validated against several datasets from healthcare environment. It provides clinicians with automated approach for enhancing quality of electronic medical records. We experimentally demonstrate that the proposed approach achieves significant enhancement over existing approaches.
Related Content
|
Bhargav Naidu Matcha, Sivakumar Sivanesan, K. C. Ng, Se Yong Eh Noum, Aman Sharma.
© 2023.
60 pages.
|
|
Lavanya Sendhilvel, Kush Diwakar Desai, Simran Adake, Rachit Bisaria, Hemang Ghanshyambhai Vekariya.
© 2023.
15 pages.
|
|
Jayanthi Ganapathy, Purushothaman R., Ramya M., Joselyn Diana C..
© 2023.
14 pages.
|
|
Prince Rajak, Anjali Sagar Jangde, Govind P. Gupta.
© 2023.
14 pages.
|
|
Mustafa Eren Akpınar.
© 2023.
9 pages.
|
|
Sreekantha Desai Karanam, Krithin M., R. V. Kulkarni.
© 2023.
34 pages.
|
|
Omprakash Nayak, Tejaswini Pallapothala, Govind P. Gupta.
© 2023.
19 pages.
|
|
|