Enhanced and Improved Disease Prediction System in Healthcare Datasets Using Machine Learning Techniques

Authors

  • Shakeel Juman T. P. Ph.D Research Scholar, Department of Computer Science, Adaikalamatha College, affiliated to Bharathidasan University Vallam, Thanjavur, Tamilnadu
  • K. Aravinthan Assistant Professor, Department of Computer Science Adaikalamatha College, affiliated to Bharathidasan University Vallam, Thanjavur, Tamilnadu

Keywords:

HDMT, IDM, CART, Clustering, Diagnosis, Data mining, Decision Making, Healthcare

Abstract

Healthcare uses Data Mining techniques (HDMT) can be for better application of knowledge and identifying successful prescription patterns for diseases. Usage of computer aided diagnosis for expert opinion learning has definite advantage. Integrated. Data Mining (IDM) with forecasting can provide a dependable and a high-quality desirable outcome. Prediction of diseases using data mining techniques is a motivating task for augmenting diagnostic accuracy. Hence the objective of this research is usage of HDMT/IDM methodology that can take less time and which can be more economical. The methodology can be useful to predict healthcare diseases. Hence to understand the usage of this research work is to identify the methodology to predict Healthcare diseases from patient’s records and suggest a non-invasive data mining model.

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References

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Published

27.12.2023

How to Cite

Juman T. P., S. ., & Aravinthan, K. . (2023). Enhanced and Improved Disease Prediction System in Healthcare Datasets Using Machine Learning Techniques. International Journal of Intelligent Systems and Applications in Engineering, 12(9s), 309–313. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/4288

Issue

Vol. 12 No. 9s (2024)

Section

Research Article

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