Diabetes Diagnosis Using Machine Learning with Cloud Security

Authors

  • Viswanath G Post-Doctoral Fellow, Srinivas University, Mangaluru, Karnataka, India. Author
  • Krishna Prasad K Professor, Institute of Engineering and Technology, Srinivas University, Mukka-574146, Karnataka, India Author
  • Dr. J Maha Lakshmi Associate Professor, MLR Institute of Technology, Dundigal, Hyderabad. Author
  • Dr.G.Swapna Assistant Professor, Apollo institute of pharmaceutical sciences, The Apollo University, Chittoor Author

DOI:

https://doi.org/10.48047/r2mhn978

Keywords:

“5G-Smart Diabetes”, ensemble classifier, XGBoost, MLP, diabetes 2”.

Abstract

This program uses open 5G technology to screen the soundness of diabetes patients at any rate cost. Countless 
people are right now burdened with diabetes because of word related pressure or ill-advised way of life decisions. People 
will stay unaware of their current wellbeing status except if they manifest side effects or get a finding through a clinical 
assessment. By then, the illness will be in a serious state, and it will be unimaginable for them to discover this data 
ahead of time. The two types of diabetes that will be available are Type 1 and Type 2 diabetes. In type 2 diabetes, 
hospitalization is fundamental; in any case, in type 1 diabetes, we can screen the patient and convey their ongoing 
condition to them or their doctors. 

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References

S. Mendis, “Global Status Report on Noncommunicable Diseases 2014,” WHO, tech. rep.; http://www.who.int/ nmh/publications/ncd-status

report-2014/en/, accessed Jan. 2015.

B. Lee, J. Kim, “Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides Based on Machine

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Published

2025-01-02

Issue

Vol. 54 No. 2 (2025): Year 2025, Volume 54, Issue 2

Section

Articles

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How to Cite

Diabetes Diagnosis Using Machine Learning with Cloud Security (V. . G, K. . Prasad K, . J. M. . Lakshmi, & G. Swapna , Trans.). (2025). Cuestiones De Fisioterapia, 54(2), 417-431. https://doi.org/10.48047/r2mhn978