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Research Article

Multi Disease Prediction System Using Machine Learning

  • Paper ID 163
  • Volume 5, Issue 3
  • Pages 112-115
  • Published Online: May-June 2024
  • 2 Views
Open Access Peer Reviewed

Authors

  • Niyati Gaur1
  • Simran Fatima2
  • Raghvendra Pratap SIngh3
  • Himanshu Patel4

1Assistant Professor, Computer Science and Engineering, School of Management Sciences, Lucknow, Uttar Pradesh, India. 234 Final Year Students, Computer Science and Engineering, School of Management Sciences, Lucknow, Uttar Pradesh, India.

Article Information

DOI
No DOI
Published Online
May-June 2024
Pages
112-115
Article Type
Research Article
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No DOI available for cross-reference

References

[1] Laxmi Deepthi Gopisetti, Srinivas Karthik Lambavai Kummera, Sai Rohan Pattamsetti, Sneha Kuna, Niharika
Parsi, Hari Priya Kodali, “Multiple Disease Prediction Model by using Machine Learning and Streamlit” 2023 IEEE,
5th International Conference on Smart Systems and Inventive Technology (ICSSIT)
[2] Akkem Yaganteeswarudu, “Multi Disease Prediction Model by using Machine Learning” 2020 IEEE, 5th International Conference
on Communication and Electronics Systems (ICCES)
[3] Elsevier B.V,” Diabetes Prediction Using Machine Learning” 2019, International Conference on Recent Trends in Advanced
Computing.
[4] KM Jyoti Rani, “Diabetes Prediction Using Machine Learning” July 2020, International Journal of Scientific Research in Computer
Science Engineering, and Information Technology
[5] Firdous, Shimoo, Wagai, Gowher A, Sharma, Kalpana, “A survey on diabetes risk prediction using machine learning approaches”,
November 2022, Journal of Family Medicine, and Primary Car.
[6] Krittanawong, C. Virk, H. U., Bengaluru, S., Wang, Z., Johnson, K. W., Pinotti, R., Zhang, H., Kaplin, S., Narasimhan, B., Kitai, T.,
Baber, U., Halperin, J. L., & Tang, W. H. (2020). Machine learning prediction in cardiovascular diseases.
[7] Chaimaa Boukhatem, Heba Yahia Youssef, Ali Bou Nassif. February 2022 IEEE, Advances in Science and Engineering Technology
International Conferences (ASET)
[8] Supriya Kamoji, Dipali Koshti, Valiant Vincent Dmello, Alrich Agnel Kudel, Nash Rajesh Vaz, Prediction of Parkinson's Disease using
Machine Learning and Deep Transfer Learning from different Feature Sets, July 2021 IEEE, 6th International Conference on
Communication and Electronics Systems (ICCES).
[9] Rohit Surya, A.T., Yaswanthram, P., Nair, P.R., Rajendra Prasath, S.S., Akella, S.V. (2022). Prediction of
Parkinson’s Disease Using Machine Learning Models—A Classifier Analysis. In: Bianchini, M., Piuri, V., Das,
S., Shaw, R.N. (eds) Advanced Computing and Intelligent Technologies. Lecture Notes in Networks and Systems, vol 218. Springer,
Singapore. https://doi.org/10.1007/978-981-16-2164-2_35.
[10] Makarious, M. B., Leonard, H. L., Vitale, D., Iwaki, H., Sargent, L., Dadu, A., Violich, I., Hutchins, E., Saffo, D., Kim, J. J., Song,
Y., Maleknia, M., Bookman, M., Nojopranoto, W., Campbell, R. H., Hashemi, S. H., Botia, J. A., Carter, J. F., Craig, D. W., . . . Nalls,
M. A. (2022). Multi-modality machine learning predicting Parkinson’s disease. Npj Parkinson's Disease, 8(1), 1-13.
https://doi.org/10.1038/s41531-022-00288-w.
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