Symptoms Based Disease Prediction Using Machine Learning

Authors

  • Revuru Ravi Teja  Department of Computer Applications, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India
  • Mr. T. Saravanan  Department of Computer Applications, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

Keywords:

Random Forest Algorithm, Naive Bayes, Support Vector Machine, Logistic regression

Abstract

People's needs for health information are changing, and more and more of them are looking for information on diseases, diagnoses, and treatments online. Review mining could reduce the amount of time needed to implement a recommendation system for physicians and medications. However, because many users lack specialized knowledge in the topic, interpreting complicated medical vocabulary might be difficult. Furthermore, the wealth of medical information available on a variety of platforms might be daunting. Providing accurate, trustworthy, and plagiarism-free content is crucial for a successful system.

References

  1. Pingale, Kedar, et al. "Disease Prediction using Machine Learning." (2019).Mr. Chala Beyene, Prof. Pooja Kamat, “Survey on Prediction and Analysis the Occurrence of Heart Disease Using Data Mining Techniques”, International Journal of Pure and Applied Mathematics, 2018.
  2. Pingale, K., Surwase, S., Kulkarni, V., Sarage, S., & Karve, A. (2019). Disease Prediction using Machine Learning.
  3. Aiyesha Sadiya, Differential Diagnosis of Tuberculosis and Pneumonia using Machine Learning (2019)
  4. S. Patel and H. Patel, “Survey of data mining techniques used in healthcare domain,” Int. J. of Inform. Sci. and Tech., Vol. 6, pp. 53-60, March, 2016.
  5. Balasubramanian, Satyabhama, and Balaji Subramanian. "Symptom based disease prediction in medical system by using Kmeans algorithm." International Journal of Advances in Computer Science and Technology 3.
  6. Dhenakaran, K. Rajalakshmi Dr SS. "Analysis of Data mining Prediction Techniques in Healthcare Management System." International Journal of Advanced Research in Computer Science and Software Engineering 5.4 (2015).
  7. Maniruzzaman, M., Rahman, M., Ahammed, B. and Abedin, M., 2020. Classification and prediction of diabetes disease using machine learning paradigm. Health information science and systems, 8(1), pp.1-14.
  8. Chen, M., Hao, Y., Hwang, K., Wang, L. and Wang, L., 2017. Disease prediction by machine learning over big data from healthcare communities. Ieee Access, 5, pp.8869-8879.
  9. Haq, A.U., Li, J.P., Memon, M.H., Nazir, S. and Sun, R., 2018. A hybrid intelligent system framework for the prediction of heart disease using machine learning algorithms. Mobile Information Systems, 2018.
  10. Keniya, R., Khakharia, A., Shah, V., Gada, V., Manjalkar, R., Thaker, T., Warang, M. and Mehendale, N., 2020. Disease prediction from various

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-08-30

Issue

Volume 9, Issue 4, July-August-2023

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Revuru Ravi Teja, Mr. T. Saravanan, " Symptoms Based Disease Prediction Using Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 4, pp.277-284, July-August-2023.