Published May 30, 2023 | Version CC BY-NC-ND 4.0
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Multiple Disease Prediction Using ML

  • 1. Professor, Department of CSE, Galgotias University Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India
  • 2. Student, Department of CSE, Galgotias University Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India.

Contributors

Contact person:

  • 1. Student, Department of CSE, Galgotias University Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India.

Description

Abstract: Accurate and on-time analysis of any health-related drawback is vital for the interference and treatment of the sickness. The normal method of diagnosing might not be sufficient within the case of a significant illness. Developing a medical diagnosing system supported machine learning (ML) algorithms for prediction of any unwellness will facilitate during a lot of correct diagnosis than the standard methodology. We've designed a disease prediction system using ML. Disease Prediction System using Machine Learning could be a system that predicts the sickness supported data or symptoms that he/she enter into the system and gives correct results supported that data. This predictive disease using Machine Learning is completed entirely with the assistance of LearningMachines and Python programing language with its Flask Interface and mistreatment antecedently offered databases with hospitals that use that we'll predict the unwellness.

Notes

Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved.

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Journal article: 2277-3878 (ISSN)

References

  • Ravi, D., Wong, C., Deligianni, F., Berthelot, M., Andreu-Perez, J., & Lo, B. et al. (2017). Deep Learning for Health Informatics. IEEE Journal of Biomedical and Health Informatics, 21(1), 4-21.
  • Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5-32.
  • Kaggle. (n.d.). Chronic Kidney Disease Dataset. Retrieved from https://www.kaggle.com/mansoordaku/ckdisease
  • Mehta, N., Pandey, S., & Verma, S. (2017). Disease Prediction System using Machine Learning over Cloud. 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), 331-336.
  • Balasubramanian, S., & Subramani, B. (2019). A system for reducing the multiple diseases showing the similar symptoms problem using machine learning techniques. Journal of Medical Systems, 43(7), 157.
  • Arya, A., Sudhanshu, & Agarwal, R. (2018). Disease prediction using machine learning algorithms. International Journal of Advanced Research in Computer Science, 9(5), 415-419.
  • Anjum, I., Afreed, M., & Kalam, M. (2020). Disease prediction using machine learning. International Journal of Advanced Science and Technology, 29(5), 1592-1601.
  • Chauhan, R. H., Naik, D. N., Halpati, R. A., Patel, S. J., & Prajapati, A. D. (2021). Disease prediction using decision tree classifier. In Proceedings of the 2021 3rd International Conference on Advances in Electronics, Computers and Communications (pp. 148-152). IEEE.

Subjects

ISSN: 2277-3878 (Online)
https://portal.issn.org/resource/ISSN/2277-3878#
Retrieval Number: 100.1/ijrte.A75680512123
https://www.ijrte.org/portfolio-item/A75680512123/
Journal Website: www.ijrte.org
https://www.ijrte.org
Publisher: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
https://www.blueeyesintelligence.org