Abstract
The CODATA Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts. The scope of the journal includes descriptions of data systems, their implementations and their publication, applications, infrastructures, software, legal, reproducibility and transparency issues, the availability and usability of complex datasets, and with a particular focus on the principles, policies and practices for open data.All data is in scope, whether born digital or converted from other sources.
Highlights
It is well known that in an Information Technology (IT) driven society, knowledge is the most significant asset of any organization
In this paper we briefly examine the impact of data mining techniques, including artificial neural networks, on medical diagnostics
A comprehensive hospital information system to meet the specific needs of a hospital contains modules for inpatient/out-patient registration, patient care, pharmacy, diet planning, accounting, etc
Summary
It is well known that in an Information Technology (IT) driven society, knowledge is the most significant asset of any organization. Sophisticated equipment used in the practice of modern medicine generates huge amount of data This data is usually stored in digital form, and considerable effort is being made to find automated methods of data analysis to generate knowledge. The area of data mining and knowledge discovery tools can play an effective role in achieving these goals (Cios & Moore, 2000). Data mining techniques can be applied to create a knowledge rich healthcare environment. In view of the large amount of medical data being generated, there is growing pressure for improved methods of data analysis and knowledge discovery using appropriate data mining techniques. A proper medical database created with intention mining can provide a useful resource for data mining and knowledge discovery. KDD is the process of finding useful information, and data mining is the process for extracting knowledge (information and patterns) derived by the KDD process using algorithms etc
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