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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM9337
Volume:
5 |
6 |
Jun 2021
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The combination of diabetes and heart disease represents a significant threat to global health, emphasizing the importance of early disease prediction for effective treatment. In this regard, there are challenges in analysing clinical data, but data science techniques offer promising solutions. Advances in healthcare technology, especially machine learning algorithms, allow valuable insights to be gained from large medical data. Integrating these algorithms into predictive models provides a new approach to disease diagnosis. In one such case, a predictive model for heart disease and diabetes was developed using a support vector classifier and logistic regression algorithms. In addition, a user-friendly graphical user interface has been created that makes it easy for medical professionals to enter patient information and obtain accurate forecasts. This acceleration includes the potential to streamline healthcare decision-making processes and improve patient outcomes through timely intervention.
KEYWORDS
Publication Date
2/15/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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