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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM30261
Volume:
8 |
4 |
Apr 2024
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.
There may be drawbacks to using traditional methods for both diagnosis and treatment, especially in the case of serious disorders. Consequently, it’s critical to have accurate and analysis of health issues in a timely manner for efficient treatment and prevention. When developing a medical diagnosis system, machine learning (ML) algorithms can be a useful tool as they can yield more accurate disease predictions than traditional approaches. Our team has effectively created a disease prediction system by utilizing multiple machine learning techniques, such as Decision trees, Naive Bayes, and KNN. We have established a framework that facilitates the creation and utilization of prediction models through the implementation of a rule-based methodology. Because of the system’s exceptional accuracy, doctors are better equipped to predict and diagnose illnesses early on and resolve health-related issues more skill fully.
KEYWORDS
Publication Date
12/31/45387
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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