Smart E-Health Prediction System Using Data Mining
G. Pooja Reddy1, M. Trinath Basu2, K. Vasanthi3, K. Bala Sita Ramireddy4, Ravi Kumar Tenali5
1G.Pooja Reddy, Department of ECM, Koneru Lakshmaih Educational Foundaton, Vaddeswaram, Guntur (A.P), India.
2M.Trinath Basu, Department of ECM, Koneru Lakshmaih Educational Foundaton, Vaddeswaram, Guntur (A.P), India.
3K.Vasanthi, Department of ECM, Koneru Lakshmaih Educational Foundaton, Vaddeswaram, Guntur (A.P), India.
4K.Bala Sita Ramireddy, Department of ECM, Koneru Lakshmaih Educational Foundaton, Vaddeswaram, Guntur (A.P), India.
5Ravi Kumar Tenali, Department of ECM, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (A.P), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 787-791 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3660048619/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In this paper, we present the techniques and applications of data mining in medicinal and instructive parts of Clinical Predictions. In medicinal and health care fields, a huge quantity of information is turning into accessible due to availability of computers. Such an oversized amount of information can’t be processed to make health predictions in the early stage and make treatment schedules to diagnose. Our aim is to assess the techniques of data processing in the fields of clinical and health care to develop correct choices. It also offers a close exchange of medicinal information handling strategies which may improve various parts of Clinical Predictions. It’s a latest powerful technology that is of high interest in the computer world. It uses already existing information in several databases to rework it into new researches and results. From huge data sets, to extract new patterns and the knowledge related to these patterns data mining uses machine learning and database management. Particularly the task is to get data by the means of automatic or semi-automatic. The various parameters enclosed in data processing include clustering, forecasting, path analysis and predictive analysis.
Keyword: Data Mining, Clinical Predictions, Machine Learning, Clustering, Predictive Analysis, Forecasting.
Scope of the Article: Data Mining Methods