A Most Efficient Health Care (HC) Based Algorithm for Prevention of Brain Disease Facets in Data Mining Applications
Naga MalleswaraRaoPurimetla1, Jaya Rama Krishnaiah V. Vemula2

1Naga MalleswaraRaoPurimetla, Research Scholar, Department of CSE, AcharyaNagarjuna University, Guntur, Andhra Pradesh, India.
2Dr. Jaya Rama Krishnaiah V. Vemula, Assoc.Professor, A.S.N. Women’s Engineering College, Tenali, Andhra Pradesh, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 4572-4577 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B5108129219/2019©BEIESP | DOI: 10.35940/ijeat.B5108.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: -Nowadays the use of data mining has been increasing rapidly in many areas like research applications, medical applications, healthcare applications, etc. The data mining applications really providing great applications for all areas due to its huge amount of data related to different types of data which was related to different types of areas in the storage servers, one of the problem with this mining applications is how to get the relevant data from the huge amount of data, many research and development applications are providing different types of solutions to retrieve the data from the mining. Once data was retrieved from the servers the users easily can solve their problems from their homes, for example, online doctor’s information systems. In the olden days when the information technology is not vastly distributed the patient doesn’t know the doctor’s availability the success percentage of doctor treatment, how many doctors are available in their city, etc. This manuscript was proposing the algorithm for the healthcare system which is called query facets algorithm, which can fetches data from the server based on the query.
Keywords: Attributes, Objects, Choice support, Traumatic cerebrum wounds, Apache hive Symbolic information investigation, Informatics, Data mining.