Prediction of Heart Diseases through Artificial Intelligence and Data Mining

AUTHORS

A V S Pavan Kumar,Dept. of Computer Science and Engineering, GIET University, Gunpur, Orissa, India

ABSTRACT

Data mining is the computational procedure of discovering styles in huge statistics sets regarding strategies on the intersection of artificial intelligence, gadget studying, facts, and database systems. It is an interdisciplinary subfield of computer technological know-how. In now a day’s lifestyle illnesses are increasing increasingly more. Data mining is one of the solutions for it, it helps us to overcome this problem by exploring old datasets. For any disease if it is identified at early stage treatment can be done easily. A wide range of data is produced in health care institutions, we will use that data to get some useful information. Data mining in medical sector helps doctors for diagnosis and treatment of diseases, this paper makes an effort to study and find interesting patterns from the data of patients.

 

KEYWORDS

Data mining, Artificial intelligence, Health care

REFERENCES

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CITATION

  • APA:
    Kumar,A.V.S.P.(2019). Prediction of Heart Diseases through Artificial Intelligence and Data Mining. International Journal of Software Engineering and Its Applications, 13(2), 17-24. 10.21742/IJSEIA.2019.13.2.03
  • Harvard:
    Kumar,A.V.S.P.(2019). "Prediction of Heart Diseases through Artificial Intelligence and Data Mining". International Journal of Software Engineering and Its Applications, 13(2), pp.17-24. doi:10.21742/IJSEIA.2019.13.2.03
  • IEEE:
    [1] A.V.S.P.Kumar, "Prediction of Heart Diseases through Artificial Intelligence and Data Mining". International Journal of Software Engineering and Its Applications, vol.13, no.2, pp.17-24, Dec. 2019
  • MLA:
    Kumar A V S Pavan. "Prediction of Heart Diseases through Artificial Intelligence and Data Mining". International Journal of Software Engineering and Its Applications, vol.13, no.2, Dec. 2019, pp.17-24, doi:10.21742/IJSEIA.2019.13.2.03

ISSUE INFO

  • Volume 13, No. 2, 2019
  • ISSN(p):1738-9984
  • ISSN(e):2208-9802
  • Published:Dec. 2019

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